Abstract: Lattice structures are receiving a renewed interest in many areas such as biomedical and industrial fields, due to the capabilities of additive manufacturing technologies which allow for the fabrication of very complex shapes. Currently, several methods and tools are described in the scientific literature and some commercial software are introducing dedicated packages to reduce designer efforts for lattice structure design and optimization. However, by using commercial CAD/CAM tools in the fabrication of components filled by lattice structure, several critical issues remain and need to be taken into consideration. This work aims at manufacturing variable-density lattice structures via fused deposition modeling deriving the density map from a grayscale or color image. In the proposed approach, the shell-based lattice model is not achieved by CAD tools, but only during the CAM process, while the lattice relative density is computed by editing the G-code, modifying the extrusion flow according to the local grayscale of a volumetric CAD model, defined from an image. The main advantages are related to the absence of a graded lattice geometric model and the consistency of the toolpath. The method is tested on various images and patterns, and can find applications in artworks, embedded information on components, and functional 3D printed parts, such as the replication of the density map of a bone derived from a DICOM grayscale image.

Keywords: Additive manufacturing | Fused deposition modeling | Graded lattices | Heterogeneous objects

Abstract: Due to the increasing number of people with severe obesity, the demand for patient-specific modelling in bariatric surgery (BS) is increasing because its potentialities in the improvement of surgical planning, optimization of outcomes and prediction of the mechanical response of the stomach. However, the patient-specific anatomical reconstruction is a pivotal and often time-consuming step due to the lack of efficient and fully automatized tools. Ongoing studies on multi-organ segmentation methods based on neural networks for magnetic resonance images (MRI) are currently available, but they have still several limits, mainly due to both the highly flexible individuals anatomical properties, and convolutional neural networks (CNN) trained only in the detection of physiological stomachs. The aim of this work is to perform a convenient transfer learning from a general-purpose CNN, able to improve the performance in automatically detecting the stomach region of patients with severe obesity. The proposed approach represents the basis for the development of pre- and post-surgical computational models for rapid clinical analysis, especially to boost the mechanical stimulation of gastric receptors. The segmentation masks and the corresponding 3D models were compared with the corresponding manual MRI segmentation as ground truth. Intersection Over Union (IOU) and DICE coefficients (DICE) were used to evaluate 2D masks segmentation, while the Relative Volume Error (RVE), mean surface distance (MSD), standard deviation and the Normalised Hausdorff distance (NHD) were applied to assess the obtained 3D results.

Keywords: Bariatric surgery | Image segmentation | MRI | Stomach

Abstract: Preface and Acknowledgements (Editorial)

Keywords: Editorial

Abstract: Objective and reliable assessment of motor functions, such as dexterity, is a key point for evaluating worker’s abilities. In this context, the proposed work presents a tool for objective automatic assessment of the Minnesota Dexterity Test using cameras with depth sensors. Typical performance measurements (i.e., total time and associated percentiles) were estimated using custom algorithms. In addition, the possibility to identify the qualifiers for the code d440 of the International Classification of Functioning, Disability and Health was implemented in the developed algorithms. The proposed tool can also identify the mistakes most frequently committed by the subjects. To prove the capabilities of the proposed method, a series of experimental trials was conducted with 10 healthy young volunteers. Results showed that the developed tool helps clinicians to obtain performance feedback and evaluate patients’ dexterity quickly without bias.

Keywords: Automatic assessment | Biomechanics | Depth cameras | Manual dexterity | Motion capture

Abstract: Post-processing pipeline for image analysis in reverse engineering modelling, such as photogrammetry applications, still asks for manual interventions mainly for shadows and reflections corrections and, often, for background removal. The usage of Convolutional Neural Network (CNN) may conveniently help in recognition and background removal. This paper presents an approach based on CNN for background removal, assessing its efficiency. Its relevance pertains to a comparison of CNN approaches versus manual assessment, in terms of accuracy versus automation with reference to cultural heritage targets. Through a bronze statue test case, pros and cons are discussed with respect to the final model accuracy. The adopted CNN is based on the U-NetMobilenetV2 architecture, a combination of two deep networks, to converge faster and achieve higher efficiency with small datasets. The used dataset consists of over 700 RGB images used to provide knowledge from which CNNs can extract features and distinguish the pixels of the statue from background ones. To extend CNN capabilities, training sets with and without dataset integration are investigated. Dice coefficient is applied to evaluate the CNN efficiency. Results obtained are used for the photogrammetric reconstruction of the Principe Ellenistico model. This 3D model is compared with a model obtained through a 3D scanner. Moreover, through a comparison with a photogrammetric 3D model obtained without the CNN background removal, performances are evaluated. Although few errors due to bad light conditions, the advantages in terms of process automation are consistent (over 50% in time reduction).

Keywords: Close range photogrammetry | CNN | Cultural heritage preservation | MobilenetV2 | Reverse engineering | U-Net

Abstract: Collaborative robots (cobots) are designed to directly interact with human beings within a shared workspace. To minimize the risk of musculoskeletal disease for the workers, a physical ergonomic assessment of their interaction is needed. Virtual reality (VR) and motion capture (Mocap) systems can aid designers in building low-hazard collaborative environments. This work presents a framework based on VR and Mocap systems for the ergonomic evaluation of collaborative robotic workstations. Starting from the 3D models of the cobot and workstation components, a virtual environment is built in Unity and ROS is employed to manage the cobot behavior. The physical ergonomics is evaluated by means of RULA methodology, exploiting the body tracking capabilities of the device Kinect Azure, a low-cost markerless Mocap system. The framework has been tested by building a virtual environment for collaborative control of flanges with different diameters. The worker interacts with a six-axis Nyro One to move parts on the workstation. The ergonomic assessment is performed in real-time, and a report is generated for later uses and evaluations. The proposed framework fosters the design of collaborative robotics workstations based on an objective assessment of ergonomics. The results of this research work allow planning future development steps for the emulation of more complex workstations with cobots and the use of augmented reality to evaluate how to modify existing workstations to introduce a cobot.

Keywords: Collaborative robots | Ergonomics | Motion capture | Virtual reality

Abstract: In this paper, a semi-automatic procedure to perform point clouds registration is presented. The method was developed for upper limb 3D scanning. During the acquisition, several frames are acquired from different points of view, to obtain a full 360° acquisition of the arm. Each frame stores both the point clouds coordinates and the corresponding RGB image. During post-processing, the RGB image is elaborated through a neural network, to detect relevant key points of the hand, which are then projected to the point clouds. The corresponding key points detected from different acquisitions are then used to automatically obtain a rough 3D rotation that aligns the point clouds corresponding to different perspectives in a common reference frame. Finally, the registration is refined through an iterative closest point algorithm. The method was tested on actual arm acquisitions, and the registration results are compared with the conventional fully manual 3-2-1 registration procedure, showing promising results of the proposed method.

Keywords: Neural network | Semi-automatic registration | Upper limb 3D scan

Abstract: Nowadays, Search and Rescue operations can be performed using manned or unmanned Aerial Vehicles. In this latter case, compact cameras are mounted onboard and a bird’s eye view is available to find the missing person. However, the analysis of the video frames can be very challenging and dull for the operators. In this context, the use of graphical methodologies can boost the searching operations and improve the process. In this study, a methodology based on the object detector Yolov5 is introduced: the performances in detecting small objects such as persons in aerial images are evaluated. These algorithms implement shallow layers of the feature extractor to increase the spatial-rich features and help the detector to find small objects. Finally, detection algorithms are tested using a video simulating a scenario for Search and Rescue operations. The filtering of frames containing false positives, is carried out using a classical graphical tool such as the Hamming distance.

Keywords: Aerial images | Graphical methodologies | Image analysis | Object detection | SAR operations

Abstract: Conventionally, visitors of exhibitions cannot directly interact with artworks but remain mainly passive. This work presents a new way to discover paintings through an extended reality application with the aim of enhancing visitors’ engagement. The workflow consists of digitally recreating a painting. All its constitutive elements are contoured and then removed by the artwork. These elements will be unveiled by the visitors with gesture interaction. The discovery of each element is followed by additional information on the subject. The application also proposes an alternative experience where the user paints the components of the artwork with gestures. The hands’ position was tracked by the Leap Motion Controller, an optical sensor by Ultraleap. The process has been applied to one of the Tintoretto’s pieces of art: “L’Annunciazione del Doge Grimani”. The extended reality application has been experienced by over twenty thousand visitors at the dedicated exhibition. Numerous positive comments received from both visitors and guides are encouraging.

Keywords: Cultural heritage | Exhibition | Extended reality | User interaction

Abstract: Anomaly detection is the identification of any event that falls outside what is considered ‘acceptable behaviour’. This work investigates anomaly detection for automated visual inspection in the context of industry automation (‘Industry 4.0’). For this task we propose a machine vision procedure based on visual feature extraction and one-class k nearest neighbours classification. The method requires only samples of normal (non-defective) instances for the training step. We benchmarked our approach using seven traditional (‘hand-designed’) colour texture descriptors and five pre-trained convolutional neural networks (CNN) ‘off-the-shelf’. Experimenting on nine image datasets from seven classes of materials (carpet, concrete, fabric, layered fused filament, leather, paper and wood), each containing normal and abnormal samples, we found overall accuracy in the range 82.0%–90.2%. Convolutional networks off-the-shelf performed generally better than the traditional methods, although – interestingly – this was not true for all the datasets considered. No visual descriptor clearly emerged as the all-purpose best option.

Keywords: Anomaly detection | Colour | Convolutional neural networks | Texture | Visual descriptors

Abstract: In the field of medical image processing, the resolution capacity exhibited by the initial diagnostic investigations is becoming increasingly important. With respect to them, in fact, the row image set is subjected to three-dimensional reconstruction analysis, by partitioning the regions of interest, as well as to local investigations, aimed, for example, at the extrapolation of topological information, relating to the morphology of the object that needs to be investigated. The accuracy of these functions is, however, difficult to quantify, due to the lack of three-dimensional models that act as a reference Gold Standard. The reproduction of CT-type diagnostic acquisitions, starting from a virtual scanning procedure of a starting known three-dimensional geometry is used. To do this, triangular tessellated three-dimensional models of various geometries were examined. These were broken down into cubic elements, equal in size to those of a common voxel, thus resulting in a volume scan simulation of the original region considered. The structure thus obtained was then subjected to skeletonization and medial axis algorithms to evaluate the effectiveness of some of the most commonly used functions in medical processing. A virtual scanning model of this type can be an extremely effective evaluation analysis tool in discriminating the resolutive quality of the medical image processing functions. From a qualitative comparison of this type, it is possible to optimize automated anatomical investigation algorithms, making a significant contribution in the refinement of the techniques, now more and more demanding, of image processing in the biomedical field.

Keywords: Medical image acquisition | Thinning and Medial Axis | Voxelization

Abstract: The comparison of the finished product's color to the color demanded by a client or provided by a catalogue is one of the most critical steps of the production of carded fibers. This is currently determined by calculating the colorimetric distance between the finished article, which is made by mixing some colored raw fibers to achieve a homogenous color, and the desired one. When this colorimetric distance exceeds a value specified by the customer, the recipe must be modified to close the gap between the end product's color and the required one. The above mentioned trial and error procedure used to determine the appropriate quantities of colored fibers for achieving a desired final color of a fiber lacks a computer-aided tool to assist colorists. Therefore, it is a bottleneck in the process of creating carded fabrics. The present work offers a novel method for predicting the spectrophotometric response of a carded fiber based on the spectrophotometric response of the raw components used to make the fiber. The method is described step-by-step. • The method is applicable to predict the spectrophotometric response of a fabric composed by any number of pre-colored fibers.

Keywords: Colour mixing | Method for predicting the spectrophotometric response of a carded fabr iccomposed by differently colored raw materials | Predictive assessment | Reflectance factors | Spectrophotometry

Abstract: Analyzing pathological movements can substantially help neurologists in the diagnosis and treatment improvement for patients with Parkinson’s disease (PD). A linkage between the intensity and characteristics of moving and walking disorders and the stage and types of PD can be actually established. The main aim of this study is to develop an effective methodology that allows to evaluate, in real time and / or in deferred time, movements and posture of PD patients in their usual living environments. For this purpose, a wearable suit with Inertial Measurement Unit (IMU) sensors was designed; it has made it possible to acquire linear and angular signals of displacement, velocity and acceleration of the most relevant body points of the patients. The filtered and integrated signals were then used to animate a human parametric multibody model that virtually reproduces in real time and / or in deferred patient’s movements and posture. Serving as the patient's “avatar”, the multibody model enables the neurologist to carry out an accurate assessment of the patient’s movements and posture (freezing, festination, postural balance) as well as to measure disease progression and response to interventions. If compared to traditional 3D video-based motion analysis systems, the proposed method has the advantage of providing a more accurately measurable patients movements analysis and comparison performed in their usual living environments in real-world conditions.

Keywords: 3D posture analysis | Human parametric multibody model | Inertial Measurement Unit sensors | Motion recognition algorithms | Parkinson’s disease movements

Abstract: The precision livestock farming (PLF) has the objective to maximize each animal's performance while reducing the environmental impact and maintaining the quality and safety of meat production. Among the PLF techniques, the personalised management of each individual animal based on sensors systems, represents a viable option. It is worth noting that the implementation of an effective PLF approach can be still expensive, especially for small and medium-sized farms; for this reason, to guarantee the sustainability of a customized livestock management system and encourage its use, plug and play and cost-effective systems are needed. Within this context, we present a novel low-cost method for identifying beef cattle and recognizing their basic activities by a single surveillance camera. By leveraging the current state-of-the-art methods for real-time object detection, (i.e., YOLOv3) cattle's face areas, we propose a novel mechanism able to detect the ear tag as well as the water ingestion state when the cattle is close to the drinker. The cow IDs are read by an Optical Character Recognition (OCR) algorithm for which, an ad hoc error correction algorithm is here presented to avoid numbers misreading and correctly match the IDs to only actually present IDs. Thanks to the detection of the tag position, the OCR algorithm can be applied only to a specific region of interest reducing the computational cost and the time needed. Activity times for the areas are outputted as cattle activity recognition results. Evaluation results demonstrate the effectiveness of our proposed method, showing a mAP@0.50 of 89%.

Keywords: Cattle identification | Computer vision | Deep learning | Low-cost sensors | Precision livestock farming

Abstract: The development of eco-sustainable systems for the textile industry is a trump card for attracting expanding markets aware of the ecological challenges that society expects in the future. For companies willing to use regenerated wool as a raw material for creating plain, colored yarns and/or fabrics, building up a number of procedures and tools for classifying the conferred recycled materials based on their color is crucial. Despite the incredible boost in automated or semi-automated methods for color classification, this task is still carried out manually by expert operators, mainly due to the lack of systems taking into account human-related classification. Accordingly, the main aim of the present work was to devise a simple, yet effective, machine vision-based system combined with a probabilistic neural network for carrying out reliable color classification of plain, colored, regenerated wool fabrics. The devised classification system relies on the definition of a set of color classes against which to classify the recycled wool fabrics and an appositely devised acquisition system. Image-processing algorithms were used to extract helpful information about the image color after a set of images has been acquired. These data were then used to train the neural network-based algorithms, which categorized the fabric samples based on their color. When tested against a dataset of fabrics, the created system enabled automatic classification with a reliability index of approximately 83%, thus demonstrating its effectiveness in comparison to other color classification approaches devised for textile and industrial fields.

Keywords: color | fabrics | machine vision | neural networks

Abstract: The experimental evaluation of welding-induced distortion is a topic of great interest to both the scientific and industrial communities. With the aim of addressing a specific need in an industrial context, this paper investigates the capabilities of a stereo–Digital Image Correlation (stereo–DIC) system to measure the weld-induced distortion of the front-plate of a bogie train bolster subassembly. Currently, the deviation from planarity of this surface is measured at less than five points using a CMM in the post-weld cooled state. An additional machining process is then used to bring the surface within the tolerance required to join the welded assembly to the train body through a threaded flange. The paper shows that DIC can provide accurate full-field distortion and strain maps over the entire 588 mm × 308 mm surface of the front plate. The distinct strength of DIC over the currently used inspection technique is its ability to provide highly spatially dense data that are unaffected by rigid body motion. This can be advantageous in terms of saving time in the post-weld inspection and reducing errors in the finishing process. In addition, DIC capabilities revealed important information that was not available from the CMM, such as the full-surface map of the initial deviation of the plate from its nominal geometry and its asymmetric deformation after welding. Finally, the full-field nature of the experimental data obtained allows for seamless integration with FE thermo-mechanical simulations for numerical model validation, stress calculation, and optimization of geometry and technological processes.

Keywords: digital image correlation | full-field distortion and strain map | traction frame | welding-induced distortion

Abstract: An area of interest in orthopaedics is the development of efficient customized neck orthoses, considered that pathologies which affect the neck area are widespread. Advanced acquisition and modelling approaches combined with Additive Manufacturing (AM) can potentially provide customized orthoses with improved performance and complexity. However, in the design of these devices, besides functional and structural requirements, benefit and comfort of the patient should be a main concern, in particular, at the early stage of design during the acquisition of the body’s part, and while using the printed orthosis. In this paper, a scanning system with three sensors was developed which allows a fast, about 5 s, and accurate acquisition of the neck area with minimum discomfort for the patient. A neck orthosis with a ventilation pattern obtained by Topology Optimization (TO), lightened by about 35%, was also established. In fact, a main role for comfort is played by the ventilation pattern which contributes both to lightness and breathability. Its structural and comfort performance was evaluated in comparison with an orthosis with a ventilation pattern configured by Voronoi cells. Structural assessment was carried out by means of finite element analysis under main loading conditions. An evaluation of neck temperatures in relation to wearing 3D printed prototypes, manufactured with Hemp Bio-Plastic® filament, was finally conducted by means of a thermal imaging camera. TO orthosis prototype showed a better performance regarding thermal comfort, with a maximum increase of neck temperature less than 1 °C, which makes the proposed configuration very promising for user's comfort.

Keywords: Additive manufacturing | CAD | Orthosis modelling | Reverse engineering | Thermal comfort | Topology optimization

Abstract: Driver posture and micro movements are main indicators of his attention and situation awareness, as well as of his capability to suddenly take control if necessary. Therefore, the real-time detection of wrong postures is essential to mitigate the risk of accidents. In this work we want to show that, by using a custom Convolutional Neural Network (CNN) for image processing, a very accurate driver posture recognition system can be realized by using a limited number of pressure sensors, grouped in a small carpet placed only on the seat of the driver, regardless of its shape. Data from the sensor carpet are converted in images reproducing the different pressure regions of the driver's body, so that the CNN can extract features and classify 8 postures with an average accuracy of 98.81% in real-time. According to the edge computing paradigm, the CNN implements an end-to-end classification by exploiting a quantization scheme for weights and binarized activations to reduce the number of required resources and allow a compact and low-power HW implementation on a small FPGA. When implemented with a Xilinx Artix 7 FPGA, the CNN consumes less than 7 mW of dynamic power at an operation frequency of 47.64 MHz. Such frequency is compatible with a sensor Output Data Rate (ODR) of 16.50 kHz, fundamental in critical applications, requiring a continuous monitoring and real-time action. Results of a 130 nm CMOS standard cells synthesis have also been reported.

Keywords: Driver safety | Neural Network | Posture recognition | Real-time image processing

Abstract: Ergonomics focuses on the analysis of the interaction between human beings and their working environment. During the riding of a motorbike, ergonomics studies the rider’s posture on the motorbike. An incorrect posture can lead to physical and psychological discomfort, and can affect the perception of risk and the handling of the motorcycle. It is important for motorcyclists to adopt a good riding posture, for their health and road safety. The aim of this work is to propose a fast, cheap, and sufficiently robust method for the 3D reconstruction of the posture assumed by a motorcyclist. The stereo vision and the application of OpenPose made it possible to obtain a 3D reconstruction of the key points, and their evolution over time. The evaluation of the distances between the 3D key points, which represent the length of the various parts of the body, appears to remain sufficiently stable over time, and faithful to the real distances, as taken on the motorcyclist themself. The 3D reconstruction obtained can be applied in different fields: ergonomics, motorsport training, dynamics, and fluid dynamics analysis.

Keywords: 3D human posture | computer vision | digital twin | ergonomics | motorsport | OpenPose | posture assessment

Abstract: Humans drive in a holistic fashion which entails, in particular, understanding dynamic road events and their evolution. Injecting these capabilities in autonomous vehicles can thus take situational awareness and decision making closer to human-level performance. To this purpose, we introduce the ROad event Awareness Dataset (ROAD) for Autonomous Driving, to our knowledge the first of its kind. ROAD is designed to test an autonomous vehicles ability to detect road events, defined as triplets composed by an active agent, the action(s) it performs and the corresponding scene locations. ROAD comprises videos originally from the Oxford RobotCar Dataset annotated with bounding boxes showing the location in the image plane of each road event. We benchmark various detection tasks, proposing as a baseline a new incremental algorithm for online road event awareness termed 3D-RetinaNet. We also report the performance on the ROAD tasks of Slowfast and YOLOv5 detectors, as well as that of the winners of the ICCV2021 ROAD challenge, which highlight the challenges faced by situation awareness in autonomous driving. ROAD is designed to allow scholars to investigate exciting tasks such as complex (road) activity detection, future event anticipation and continual learning. The dataset is available at https://github.com/gurkirt/road-dataset; the baseline can be found at https://github.com/gurkirt/3D-RetinaNet.

Keywords: action detection | Autonomous driving | Autonomous vehicles | Benchmark testing | decision making | Decision making | road agents | Roads | situation awareness | Task analysis | Vehicle dynamics | Videos

Abstract: Background and Objective:In biomedical fields, image analysis is often necessary for an accurate diagnosis. In order to obtain all the information needed to form an in-depth clinical picture, it may be useful to combine the contents of images taken under different diagnostic modes. Multimodal medical image fusion techniques enable complementary information acquired by different imaging devices to be automatically combined into a unique image. Methods:In this paper, multimodal medical images fusion method based on multiresolution analysis (MRA) is proposed, with the aim to combine the high geometric content of magnetic resonance imaging (MRI) and the elasticity information of magnetic resonance elastography (MRE), simultaneously acquired on the same organs of a patient. First, the slices of MRE are volumetrically interpolated to exactly overlap, each with a slice of MRI. Then, the spatial details of MRI are extracted by means of MRA and injected into the corresponding slices of MRE. Due to the intrinsic dissimilarity between corresponding slices of MRE and MRI, the spatial details of MRI are modulated by local or global matching functions. Results:The performance of the proposed method is quantitatively assessed considering radiometric and geometric consistency of the fused images with respect to their originals, in a comparison with two popular methods from the literature. For a qualitative evaluation, a visual inspection is carried out. Conclusions:The results show that the proposed method enables an effective MRI-MRE fusion that allows the elasticity information and geometric details of the examined organs to be evaluated in a single image.

Keywords: Biomedical images | Image processing | Magnetic resonance elastography | Multimodal fusion | Multiresolution analysis | Tomographic sequences

Abstract: In this paper an interactive computational methodology was developed assuming that shape and size optimization of flexible components can significantly improve energy absorption or storage ability in assembled systems with flexible components (AS-FC). A radial basis functions mesh morphing formulation in non-linear numerical finite element analysis, including contact problems and flow interaction, was adopted as optimal design method to optimize shape and size design parameters in AS-FC. Flexible components were assembled in finite element environment according to functional ISO-ASME tolerances specification; non-linear structural analysis with flow interaction analysis was performed. The results of the study showed that the proposed method allows to optimize the shape and size of the flexible components in AS-FC maximizing the system's ability to absorb or store energy. The potentiality of the method and its forecasting capability were discussed for the case study of an automotive crash shock in which the specific energy absorption was increased by over 40%. The case studied refers to a simple flexible component geometry, but the method could be extended to systems with more complex geometries.

Keywords: Crash shock absorber | ISO-ASME tolerances specification | Radial basis functions | Shape and size optimization | Specific energy absorption

Abstract: In the Cultural Heritage field, the choice of materials and exhibit structures is essential to properly house and support artifacts without causing damage or deterioration. This problem is even more evident in the case of finds made of stone for which, due to their weight, a proper selection and dimensioning of the relative supports is required. In fact, without adequate support, this can result in stress concentrations that could compromise the artifact's state of conservation. As a consequence, more often such exhibition supports are customized items, that are designed and manufactured to meet specific functional and artistic setup needs. In this context, the paper presents a design approach that combines topology optimization and additive manufacturing techniques to develop customized support structures which undertake the twofold purpose of preserving the artifact and making it available for the exhibition in the museum. The proposed approach has been assessed through the case study of a sandstone Ionic capital hosted in the Brettii & Enotri Museum in Cosenza (Italy). The proposed approach is therefore meant as a guideline for the design of customized exhibit supports especially in the case of sandstone artifacts with a complex shape or a conservation condition that requires specific attention.

Keywords: Additive manufacturing | Cultural heritage | Design methods | Exhibit supports | Photogrammetry | Topology optimization

Abstract: Although computer vision techniques are widely and effectively used for terrestrial applications, the adoption of these techniques in underwater scenarios is often a challenging task. This is due to the water medium that degrades the quality of the acquired images requiring the use of specific methodologies for their correction and improvement. In this context, this paper presents a low-cost system for underwater 3D reconstruction and 3D measurements based on an off-the-shelf depth camera. The system consists of a Stereolabs ZED stereo camera and its waterproof housing designed to be fabricated through additive manufacturing technologies. A dedicated software has been developed to manage all the steps of the acquisition process, starting from the calibration phase and continuing for rectification, depth map computation, 3D scene reconstruction, and 3D measurement. A preliminary laboratory test has been carried out in a controlled environment to quantify system performance in accuracy of measurement.

Keywords: Calibration Techniques | Stereo Camera | Stereolabs ZED | Underwater 3D Reconstruction | Underwater Inspection

Abstract: Indeterminate lung nodules detected on CT scans are common findings in clinical practice. Their correct assessment is critical, as early diagnosis of malignancy is crucial to maximise the treatment outcome. In this work, we evaluated the role of form factors as imaging biomarkers to differentiate benign vs. malignant lung lesions on CT scans. We tested a total of three conventional imaging features, six form factors, and two shape features for significant differences between benign and malignant lung lesions on CT scans. The study population consisted of 192 lung nodules from two independent datasets, containing 109 (38 benign, 71 malignant) and 83 (42 benign, 41 malignant) lung lesions, respectively. The standard of reference was either histological evaluation or stability on radiological followup. The statistical significance was determined via the Mann–Whitney U nonparametric test, and the ability of the form factors to discriminate a benign vs. a malignant lesion was assessed through multivariate prediction models based on Support Vector Machines. The univariate analysis returned four form factors (Angelidakis compactness and flatness, Kong flatness, and maximum projection sphericity) that were significantly different between the benign and malignant group in both datasets. In particular, we found that the benign lesions were on average flatter than the malignant ones; conversely, the malignant ones were on average more compact (isotropic) than the benign ones. The multivariate prediction models showed that adding form factors to conventional imaging features improved the prediction accuracy by up to 14.5 pp. We conclude that form factors evaluated on lung nodules on CT scans can improve the differential diagnosis between benign and malignant lesions.

Keywords: computed tomography | form factors | lung cancer | radiomics

Abstract: Hepatic diseases are serious condition worldwide, and several times doctors analyse the situation and elaborates a preoperative planning based exclusively on the medical images, which are a drawback since they only provide a 2D vision and the location of the damaged tissues in the three-dimensional space cannot be easily determined by surgeons. Nowadays, with the advancement of Computer Aided Design (CAD) technologies and image segmentation, a digital liver model can be obtained to help understand the particular medical case; even with the geometric model, a virtual simulation can be elaborated. This work is divided into two phases; the first phase involves a workflow to create a liver geometrical model from medical images. Whereas the second phase provides a methodology to achieve liver prototype, using the technique of fused deposition modelling (FDM). The two stages determine and evaluate the most influencing parameters to make this design repeatable in different hepatic diseases. The reported case study provides a valuable method for optimizing preoperative plans for liver disease. In addition, the prototype built with additive manufacturing will allow the new doctors to speed up their learning curve, since they can manipulate the real geometry of the patient's liver with their hands.

Keywords: 3D printing | Convolutional neural network | FDM | Image segmentation | Liver disease

Abstract: There is a large body of research devoted to identifying the complexity of structures in networks. In the context of network theory, a complex network is a graph with nontrivial topological features—features that do not occur in simple networks, such as lattices or random graphs, but often occur in graphs modeling real systems. The study of complex networks is a young and active area of scientific research inspired largely by the empirical study of real-world networks, such as computer networks and logistic transport networks. Transport is of great importance for the economic and cultural cooperation of any country with other countries, the strengthening and development of the economic management system, and in solving social and economic problems. Provision of the territory with a well-developed transport system is one of the factors for attracting population and production, serving as an important advantage for locating productive forces and providing an integration effect. In this paper, we introduce a new method for quantifying the complexity of a network based on presenting the nodes of the network in Cartesian coordinates, converting to polar coordinates, and calculating the fractal dimension using the ReScaled ranged (R/S) method. Our results suggest that this approach can be used to determine complexity for any type of network that has fixed nodes, and it presents an application of this method in the public transport system.

Keywords: complexity | fractal | Hurst exponent H | network | public transport

Abstract: The compression behaviour in quasi-static and dynamic conditions of cellular materials is crucial for their applications both for ensuring structural strength and high energy absorption capability. Despite the recent progress made in understanding the experimental observations, analytical and numerical modelling still requires improvements in the Representative Volume Element (RVE) identification that can be uncertain due to the limited dimensions of the investigated specimens and to the cell inhomogeneity. The objective of this paper is to implement a material model able to consider the statistical distribution so that its effect can be quantitatively highlighted, mitigating uncertainty of the RVE identification. The applied methodology started with morphological and topological analyses on samples extracted from an ingot of AA7075T6 foam, which was manufactured by compact powder technology. Quasi-static and dynamic experimental compression tests have been carried out and compared with 3D mesoscale numerical simulations in order to correlate the mechanical behaviour of the foam to the cell characteristics. Finally, an equivalent material model, which is a function of the statistical distributions of cells morphology and topology, has been proposed and analytically verified.

Keywords: Aluminium foam | Cellular material | High strain rate | Homogeneous formulation | RVE | SHPB

Abstract: In hip arthroplasty, preoperative planning is fundamental to reaching a successful surgery. Nowadays, several software tools for computed tomography (CT) image processing are available. However, research studies comparing segmentation tools for hip surgery planning for patients affected by osteoarthritic diseases or osteoporotic fractures are still lacking. The present work compares three different software from the geometric, dimensional, and usability perspectives to identify the best three-dimensional (3D) modelling tool for the reconstruction of pathological femoral heads. Syngo.via Frontier (by Siemens Healthcare) is a medical image reading and post-processing software that allows low-skilled operators to produce prototypes. Materialise (by Mimics) is a commercial medical modelling software. 3D Slicer (by slicer.org) is an open-source development platform used in medical and biomedical fields. The 3D models reconstructed starting from the in vivo CT images of the pathological femoral head are compared with the geometries obtained from the laser scan of the in vitro bony specimens. The results show that Mimics and 3D Slicer are better for dimensional and geometric accuracy in the 3D reconstruction, while syngo.via Frontier is the easiest to use in the hospital setting.

Keywords: bio-imaging | CT image segmentation | hip surgery | orthopaedics | reverse engineering | software comparison | surgical planning

Abstract: This paper introduces a system that enable the collection of relevant data related to the emotional behavior and attention of both student and professor during exams. It exploits facial coding techniques to enable the collection of a large amount of data from the automatic analysis of students and professors faces using video analysis, advanced techniques for gaze tracking based on deep Learning, and technologies and the principles related to the Affective Computing branch derived from the research of Paul Ekman. It provides tools that facilitates the interpretation of the collected data by means of a dashboard. A preliminary experiment has been carried out to investigate whether such a system may help in assessing the evaluation setting and support reflection on the evaluation processes in the light of the different situations, so as to improve the adoption of inclusive approaches. Results suggest that information provided by the proposed system can be helpful in assessing the setting and the evaluation process.

Keywords: Affective computing | Deep learning | E-leaning | Emotion recognition | Gaze tracking

Abstract: Facial appearance is one prominent feature in analyzing several aspects, e.g., aesthetics and expression of emotions, and face analysis is crucial in many fields. Face analysis requires measurements that can be performed by different technologies and typically relies on landmarks identification. Recently, low-cost customer grade 3D cameras have been introduced in the market, enabling an increase of application at affordable cost with nominal adequate performances. Novel cameras require to be thoroughly metrologically characterized to guarantee these performances. Cameras are calibrated following a standard general-purpose procedure. However, the specificity of facial measurements requires a task-based metrological characterization to include typical influence factors. This work outlines a methodology for task-based metrological characterization of low-cost 3D cameras for facial analysis, consisting of: influence factor identification by ANOVA, related uncertainty contribution assessment, uncertainty propagation, landmarking uncertainty estimation. The proposed methodology is then demonstrated on a customer grade state-of-the-art 3D camera available on the market.

Keywords: Depth cameras | Face analysis | Human-machine interaction | Machine vision | Measurement uncertainty | Soft tissue landmarks

Abstract: A low-speed stereo-camera DIC setup was used in this paper to measure the down-sampled bandpass vibration signal of a plate in a given frequency range, which is much higher than the available frame rate. Down-sampled vibration measurements are well known in the literature. However, they are always subject to the strong hypothesis of having a single frequency component in the excitation source (e.g., pure sinusoidal excitation). In this scenario, several approaches can be found in the literature to reconstruct the actual response from the down-sampled data. In this paper, a data postprocessing algorithm is newly introduced to properly reconstruct the target response in the case of a frequency band excitation, thus relaxing the single frequency excitation constraint and allowing to explore a given frequency range with a single measurement. Additionally, a custom excitation signal is presented in this paper to achieve a constant intensity in the studied frequency range. The proposed approach is presented and experimentally validated by measuring a cantilever plate vibration in the kHz range using a 100 fps acquisition. A single acquisition of 98 frames allowed to describe the deformed shapes at 49 different frequency values in the range 1110–1160 Hz, highlighting two resonance peaks. The comparison with the results of multiple conventional single-frequency tests and LDV measurements confirmed the effectiveness of the proposed approach.

Keywords: Digital image correlation | Down-sampled bandpass measurement | Frequency band excitation | Low-speed camera | Vibration measurement

Abstract: The digital image correlation (DIC) was used in this paper to obtain full-field measurements of a target vibrating at a frequency higher than the maximum cameras’ frame rate. The down-sampling technique was implemented to compensate for the cameras’ moderate frame rate, thus getting an accurate displacement acquisition even at 6.5 kHz. Two innovative methods to support the DIC application were introduced. The use of fringe projection (or structured light), initially applied on the sample at rest, reduced the effort and time required for the stereo matching task's solution and improved this setting's accuracy and reliability. Additionally, a new time-domain image filtering was proposed and tested to improve the quality of the obtained DIC maps. In combination with the down-sampling, the effect of this filtering technique was tested in this work at (approx.) 2500 and 6500 Hz by measuring the response of a bladed disk to sinusoidal excitation. Evidence of improved results was observed for both frequencies for amplitudes in the range of 10 µm.

Keywords: Bladed disk | Digital image correlation | Down-sampling approach | Low-speed camera | Reverse engineering | Vibration measurement

Abstract: Shearlet is a multi-dimensional function used for sparse representation, which has many excellent characteristics such as multi-resolution and multi-direction. It can detect the position of singular points and the direction of singular curves, and is more sensitive to the geometric structure of the image. Therefore, this paper introduces the shearlet transform and its application in image processing, and introduces the bendlet transform proposed on this basis.

Keywords: Bendlet | Image processing | Shearlet | Transform

Abstract: Emotion recognition through machine learning techniques is a widely investigated research field, however the recent obligation to wear a face mask, following the COVID19 health emergency, precludes the application of systems developed so far. Humans naturally communicate their emotions through the mouth; therefore, the intelligent systems developed to date for identifying emotions of a subject primarily rely on this area in addition to other anatomical features (eyes, forehead, etc.). However, if the subject is wearing a face mask this region is no longer visible. For this reason, the goal of this work is to develop a tool able to compensate for this shortfall. The proposed tool uses the AffectNet dataset which is composed of eight class of emotions. The iterative training strategy relies on well-known convolutional neural network architectures to identify five sub-classes of emotions: following a pre-processing phase the architecture is trained to perform the task on the eight-class dataset, which is then recategorized into five classes allowing to obtain 96.92% of accuracy on the testing set. This strategy is compared to the most frequently used learning strategies and finally integrated within a real time application that allows to detect faces within a frame, determine if the subjects are wearing a face mask and recognize for each one the current emotion.

Keywords: Artificial intelligence | COVID19 | Emotion recognition | Facial Expression Recognition | Grad-CAM | Non-verbal communication

Abstract: This paper introduces a web-platform system that performs semi-automatic compute of several risk indexes, based on the considered evaluation method (e.g., RULA—Rapid Upper Limb Assessment, REBA—Rapid Entire Body Assessment, OCRA—OCcupational Repetitive Action) to support ergonomics risk estimation, and provides augmented analytics to proactively improve ergonomic risk monitoring based on the characteristics of workers (e.g., age, gender), working tasks, and environment. It implements a body detection system, marker-less and low cost, based on the use of RGB cameras, which exploits the open-source deep learning model CMU (Carnegie Mellon University), from the tf-pose-estimation project, assuring worker privacy and data protection, which has been already successfully assessed in standard laboratory conditions. The paper provides a full description of the proposed platform and reports the results of validation in a real industrial case study regarding a washing machine assembly line composed by 5 workstations. A total of 15 workers have been involved. Results suggest how the proposed system is able to significantly speed up the ergonomic assessment and to predict angles and perform a RULA and OCRA analysis, with an accuracy comparable to that obtainable from a manual analysis, even under the unpredictable conditions that can be found in a real working environment.

Keywords: Ergonomics risk assessment | Extended reality | Human-centered manufacturing | Machine learning | Motion capture

Abstract: Qualitative and quantitative analysis of surface defects on aluminum die-cast parts is important for both quality assurance and process monitoring. In addition to the functionality and durability of the parts, the appearance of a die-cast component can be of crucial importance during the inspection of incoming goods by customers in order to ensure their functionality. Nowadays, many of the detection operations of surface defects are performed by specialized operators, but this approach is far from being sustainable for high production rates. In this context, research has focused on machine vision systems for automatic defect detection based on artificial intelligence (AI) and artificial neural networks. However, several obstacles have so far hindered a full-scale application of these intelligent systems. Images of the aluminum surface can contain a large amount of noise due to surface reflectivity and, in addition, vibrations, improper/variable ambient lighting can make automatic analysis of surface defects, which usually have an irregular shape, very difficult. This led to combining the potential of 3D scanning and measuring systems with 2D machine vision as an acquisition technology to detect surface defects. Nevertheless, the two acquisition processes present strengths and weaknesses, which mostly depend on geometrical aspects of the parts to be detected. The present paper illustrates a first attempt to combine the mentioned 2D and 3D systems into an industrial production environment. The paper presents the developed system to allow multiple acquisitions and explains how these sources of information are fed to an AI system.

Keywords: Artificial intelligence | Deep learning | High-pressure die-casting | Machine vision systems | Quality control | Surface defects analysis

Abstract: Radiological examination of pulmonary nodules on CT involves the assessment of the nodules’ size and morphology, a procedure usually performed manually. In recent years computer-assisted analysis of indeterminate lung nodules has been receiving increasing research attention as a potential means to improve the diagnosis, treatment and follow-up of patients with lung cancer. Computerised analysis relies on the extraction of objective, reproducible and standardised imaging features. In this context the aim of this work was to evaluate the correlation between nine IBSI-compliant morphological features and three manually-assigned radiological attributes – lobulation, sphericity and spiculation. Experimenting on 300 lung nodules from the open-access LIDC-IDRI dataset we found that the correlation between the computer-calculated features and the manually-assigned visual scores was at best moderate (Pearson’s r between -0.61 and 0.59; Spearman’s ρ between -0.59 and 0.56). We conclude that the morphological features investigated here have moderate ability to match/explain manually-annotated lobulation, sphericity and spiculation.

Keywords: Lung cancer | Morphological features | Pulmonary nodules | Radiomics

Abstract: Image registration has widespread application in fields like medical imaging, satellite imagery and agriculture precision as it is essential for feature detection and extraction. The extent of this paper is focussed on analysis of intensity and feature-based registration algorithms over Blue and RedEdge multispectral images of wheat and cauliflower field under different altitudinal conditions i.e., drone imaging at 3 m for cauliflower and handheld imaging at 1 m for wheat crops. The overall comparison among feature and intensity-based algorithms is based on registration quality and time taken for feature matching. Intra-class comparison of feature-based registration is parameterized on type of transformation, number of features being detected, number of features matched, quality and feature matching time. Intra-class comparison of intensity-based registration algorithms is based on type of transformation, nature of alignment, quality and feature matching time. This study has considered SURF, MSER, KAZE, ORB for feature-based registration and Phase Correlation, Monomodal intensity and Multimodal intensity for intensity-based registration. Quantitatively, feature-based techniques were found superior to intensity-based techniques in terms of quality and computational time, where ORB and MSER scored highest. Among intensity-based methods, Monomodal intensity performed best in terms of registration quality. However, Phase Correlation marginally scored less in quality but fared well in terms of computational time.

Keywords: Control points (CP) | Feature transform (SIFT) | Feature-based | Intensity-based | KAZE | Maximally Stable Extremal Regions (MSER) | Modified difference local binary (MDLB) | Monomodal | Multi spectral (MS) | Multimodal | Mutual information (MI) | Normalized cross correlation | Oriented Fast and Rotated Brief (ORB) | Phase correlation | Scale-invariant (SI) | Speeded Up Robust Features (SURF) | Sum of squared differences (SSD)

Abstract: Small-scale experimental tests were carried out by a bi-disc machine to reproduce the phenomena occurring in shoe-braked railway wheels. Wheel specimens of three different steels were subjected first to a braking step against cast iron brake-block specimens in full sliding condition, then to a running step against a rail steel in rolling-sliding condition. To monitor the damage occurring at the wheel specimen surface, a vision system, based on a high-speed camera acquiring the surface images during the tests, was implemented. An image analysis procedure was elaborated to evaluate the surface state by means of quantitative synthetic indexes. The correlation of such indexes with the damage was validated by means of comparison with the subsurface state, obtained by optical microscope observation of cut specimens. Finally, the synthetic indexes were used to analyse the evolution of the damage on a long-duration test, proving to be effective as a non-destructive damage monitoring tool.

Keywords: Bi-disc tests | Damage analysis | Railway wheel steels | Shoe-braking | Vision system

Abstract: Tests in alternated dry-wet contact were carried out by a bi-disc machine on specimens extracted from railway wheels. Some of them were cylindrical, other ones were crowned: cylindrical-cylindrical and crowned-cylindrical couplings were tested. The surface appearance was acquired by a vision system; the acquired images were elaborated to extract quantitative damage indexes. In cylindrical-cylindrical coupling, the damage increased in alternated dry-wet sessions as far as the cycle number increased, whereas it was stabilized in long dry sessions. In crowned-cylindrical couplings, the damage tended to decrease as far as the cycles increased, in all the test conditions. The contact patch width in crowned-cylindrical coupling increased as far as the cycle number increased: this led the overall stress state to decrease, this way mitigating the damage.

Keywords: damage monitoring | dry-wet contact | Railway wheel steel | rolling contact tests | vision system

Abstract: Convolutional neural networks are increasingly used in the medical field for the automatic segmentation of several anatomical regions on diagnostic and non-diagnostic images. Such automatic algorithms allow to speed up time-consuming processes and to avoid the presence of expert personnel, reducing time and costs. The present work proposes the use of a convolutional neural network, the U-net architecture, for the segmentation of ear elements. The auricular elements segmentation process is a crucial step of a wider procedure, already automated by the authors, that has as final goal the realization of surgical guides designed to assist surgeons in the reconstruction of the external ear. The segmentation, performed on depth map images of 3D ear models, aims to define of the contour of the helix, antihelix, tragus-antitragus and concha. A dataset of 131 ear depth map was created;70% of the data are used as the training set, 15% composes the validation set, and the remaining 15% is used as testing set. The network showed excellent performance, achieving 97% accuracy on the validation test.

Abstract: A major challenge in the field of Augmented Reality (AR) is the way in which augmented information is presented in a wide range of uncontrollable environmental conditions. In fact, the variability of colours and illumination conditions of the real environment makes it difficult to choose the most suitable appearance properties for augmented contents. In many AR applications, the colours of virtual objects play a crucial role in blending digital information into the real environment, therefore these colours should be selected according to the appearance of the real background. In some use cases, the colours of virtual objects need to be harmonised with the ones of the real environment; in other cases, the colours should be chosen to ensure the visibility (e.g. maximizing the contrast) of the augmented data with respect to the background. To this end, the paper presents a background-aware colourisation technique that allows for selecting virtual objects' colours in accordance with the real environment in real-time. Given an arbitrary real background, virtual objects' colours are automatically chosen according to three different strategies, i.e. harmonic, disharmonic, and balanced. The proposed AR colourisation technique was assessed with a user study that focused on three different case studies. The results were promising and suggest the potential of the proposed technique for many different application areas. In particular, disharmonic and balanced strategies ensured the distinctiveness of virtual objects according to the real background. Instead, the harmonic strategy was less effective in the case of colourful complex AR scenarios.

Keywords: Augmented reality | colour harmonisation | colourisation | image processing | user studies

Abstract: Colour and texture are two perceptual stimuli that determine, to a great extent, the appearance of objects, materials and scenes. The ability to process texture and colour is a fundamental skill in humans as well as in animals; therefore, reproducing such capacity in artificial (‘intelligent’) systems has attracted considerable research attention since the early 70s. Whereas the main approach to the problem was essentially theory-driven (‘hand-crafted’) up to not long ago, in recent years the focus has moved towards data-driven solutions (deep learning). In this overview we retrace the key ideas and methods that have accompanied the evolution of colour and texture analysis over the last five decades, from the ‘early years’ to convolutional networks. Specifically, we review geometric, differential, statistical and rank-based approaches. Advantages and disadvantages of traditional methods vs. deep learning are also critically discussed, including a perspective on which traditional methods have already been subsumed by deep learning or would be feasible to integrate in a data-driven approach.

Keywords: Colour | Deep learning | Texture | Visual recognition

Abstract: Computer-assisted analysis of three-dimensional imaging data (radiomics) has received a lot of research attention as a possible means to improve the management of patients with lung cancer. Building robust predictive models for clinical decision making requires the imaging features to be stable enough to changes in the acquisition and extraction settings. Experimenting on 517 lung lesions from a cohort of 207 patients, we assessed the stability of 88 texture features from the following classes: first-order (13 features), Grey-level Co-Occurrence Matrix (24), Grey-level Difference Matrix (14), Grey-level Run-length Matrix (16), Grey-level Size Zone Matrix (16) and Neighbouring Grey-tone Difference Matrix (five). The analysis was based on a public dataset of lung nodules and open-access routines for feature extraction, which makes the study fully reproducible. Our results identified 30 features that had good or excellent stability relative to lesion delineation, 28 to intensity quantisation and 18 to both. We conclude that selecting the right set of imaging features is critical for building clinical predictive models, particularly when changes in lesion delineation and/or intensity quantisation are involved.

Keywords: Computed tomography | Intensity quantisation | Lesion delineation | Lung nodules | Radiomics | Stability | Texture features

Abstract: This study shows the application of a system to monitor the state of damage of railway wheel steel specimens during rolling contact fatigue tests. This system can make continuous measurements with an evaluation of damage without stopping the tests and without destructive measurements. Four tests were carried out to train the system by recording torque and vibration data. Both statistical and spectral features were extracted from the sensors signals. A Principal Component Analysis (PCA) was performed to reduce the volume of the initial dataset; then, the data were classified with the k-means algorithm. The results were then converted into probabilities curves. Metallurgical investigations (optical micrographs, wear curves) and hardness tests were carried out to assess the trends of machine learning analysis. The training tests were used to train the proposed algorithm. Three validation tests were performed by using the real-time results of the k-means algorithm as a stop condition. Metallurgical analysis was performed also in this case. The validation tests follow the results of the training test and metallurgical analysis confirms the damage found with the machine learning analysis: when the membership probability of the cluster corresponding to the damage state reaches a value higher than 0.5, the metallurgical analysis clearly shows the cracks on the surface of the specimen due to the rolling contact fatigue (RCF) damage mechanism. These preliminary results are positive, even if reproduced on a limited set of specimens. This approach could be integrated in rolling contact fatigue tests to provide additional information on damage progression.

Keywords: Damage assessment | Machine learning | Metallurgical analysis | Rolling contact fatigue tests

Abstract: A vision-based experimental methodology was developed for monitoring the surface state evolution of specimens during twin-disc rolling contact tests, aimed at providing information for identifying the damage phenomena. The system is based on a high-speed camera and three laser pointers for illuminating the specimen surface. Images of the specimen surface are acquired and processed, allowing the definition of synthetic surface state indexes, as well as the section profiles of the surface. The vision system was applied to alternated dry–wet rolling–sliding contact tests on railway wheel steel specimens, highlighting its effectiveness in the damage evaluation. The potential of the section profile reconstruction as a tool for surface topology analysis was shown.

Keywords: damage assessment | image processing | Online monitoring | rolling contact fatigue | wear

Abstract: The study of the human body and its movements is still a matter of great interest today. Most of these issues have as their fulcrum the study of the balance characteristics of the human body and the determination of its Centre of Mass. In sports, a lot of attention is paid to improving and analysing the athlete's performance. Almost all the techniques for determining the Centre of Mass make use of special sensors, which allow determining the physical magnitudes related to the different movements made by athletes. In this paper, a markerless method for determining the Centre of Mass of a subject has been studied, comparing it with a direct widely validated equipment such as the Wii Balance Board, which allows determining the coordinates of the Centre of Pressure. The Motion Capture technique was applied with the OpenPose software, a Computer Vision method boosted with the use of Convolution Neural Networks. Ten quasi-static analyses have been carried out. The results have shown an error of the Centre of Mass position, compared to that obtained from the Wii Balance Board, which has been considered acceptable given the complexity of the analysis. Furthermore, this method, despite the traditional methods based on the use of balances, can be used also for prediction of the vertical position of the Centre of Mass.

Keywords: 3D motion capture | Convolution neural networks | Open Pose

Abstract: This paper introduces a low-cost and low computational marker-less motion capture system based on the acquisition of frame images through standard RGB cameras. It exploits the open-source deep learning model CMU, from the tf-pose-estimation project. Its numerical accuracy and its usefulness for ergonomic assessment are evaluated by a proper experiment, designed and per-formed to: (1) compare the data provided by it with those collected from a motion capture golden standard system; (2) compare the RULA scores obtained with data provided by it with those obtained with data provided by the Vicon Nexus system and those estimated through video analysis, by a team of three expert ergonomists. Tests have been conducted in standardized laboratory conditions and involved a total of six subjects. Results suggest that the proposed system can predict angles with good consistency and give evidence about the tool’s usefulness for ergonomist.

Keywords: Ergonomic risk assessment | Industrial ergonomics | Motion capture | Postural analysis | RULA

Abstract: Driver behaviour recognition is of paramount importance for in-car automation assistance. It is widely recognized that not only attentional states, but also emotional ones have an impact on the safety of the driving behaviour. This research work proposes an emotion-aware in-car architecture where it is possible to adapt driver’s emotions to the vehicle dynamics, investigating the correlations between negative emotional states and driving performances, and suggesting a system to regulate the driver’s engagement through a unique user experience (e.g. using music, LED lighting) in the car cabin. The relationship between altered emotional states induced through auditory stimuli and vehicle dynamics is investigated in a driving simulator. The results confirm the need for both types of information to improve the robustness of the driver state recognition function and open up the possibility that auditory stimuli can modify driving performance somehow.

Keywords: Driver monitoring system | Emotion recognition | Facial expression recognition

Abstract: This paper introduces a new recommendation system for museums able to profile the visitors and propose them the most suitable exhibition path accordingly, to improve visitors’ satisfaction. It consists of an interactive touch screen totem, which implements a USB camera and exploits Convolutional Neural Network to perform facial coding to measure visitors’ emotions and estimate their age and gender. Based on the detected level of emotional valence, the system associates visitors with a profile and suggests them to visit a selection of five works of art, following a specific itinerary. An extensive experimentation lasting 2 months has been carried out at the Modern Art Museum “Palazzo Buonaccorsi” of Macerata. Results evidence that the proposed system can create an interactive and emotional link with the visitors, influencing their mood in the Pre-Experience phase and in the subsequent Post-Experience phase. In particular, they highlight that the proposed system, which aims at acting as emotional leverage, has been able to improve the positiveness of the emotions experienced by the visitors.

Keywords: Affective computing | Cultural heritage | Emotion recognition | Facial expression recognition

Abstract: Vibration measurements of turbomachinery components are of utmost importance to char-acterize the dynamic behavior of rotating machines, thus preventing undesired operating conditions. Local techniques such as strain gauges or laser Doppler vibrometers are usually adopted to collect vibration data. However, these approaches provide single-point and generally 1D measurements. The present work proposes an optical technique, which uses two low-speed cameras, a multimedia projector, and three-dimensional digital image correlation (3D-DIC) to provide full-field measurements of a bladed disk undergoing harmonic response analysis (i.e., pure sinusoidal excitation) in the kHz range. The proposed approach exploits a downsampling strategy to overcome the limitations introduced by low-speed cameras. The developed experimental setup was used to measure the response of a bladed disk subjected to an excitation frequency above 6 kHz, providing a deep insight in the deformed shapes, in terms of amplitude and phase distributions, which could not be feasible with single-point sensors. Results demonstrated the system’s effectiveness in measuring amplitudes of few microns, also evidencing blade mistuning effects. A deeper insight into the deformed shape analysis was provided by considering the phase maps on the entire blisk geometry, and phase variation lines were observed on the blades for high excitation frequency.

Keywords: Bladed disk vibration | Digital image correlation | Downsampling | Low-speed cameras | Mistuning

Abstract: Color schemes play a crucial role in blending virtual objects with the real environment. Good color schemes improve user’s perception, which is of crucial importance for augmented reality. In this paper, we propose a set of novel methods based on the color harmonization methodology to recolor augmented reality content according to the real background. Three different strategies are proposed—harmonic, disharmonic, and balance—that allow for satisfying different needs in different settings depending on the application field. The first approach aims to harmonize the colors of virtual objects to make them consistent with the colors of the real background and reach a more pleasing effect to a human eye. The second approach, instead, can be adopted to generate a set of disharmonious colors with respect to real ones to be associated with the augmented virtual content to improve its distinctiveness from the real background. The third approach balances these goals by achieving a compromise between harmony and good visibility among virtual and real objects. Furthermore, the proposed re-coloring method is applied to three different case studies by adopting the three strategies to meet three different objectives, which are specific for each case study. Several parameters are calculated for each test, such as the covered area, the color distribution, and the set of generated colors. Results confirm the great potential of the proposed approaches to improve the AR visualization in different scenarios.

Keywords: Augmented reality | Color harmonization | Image processing

Abstract: Motion capture (Mocap) systems are considered more and more interesting for the assessment of rehabilitation processes. In fact, medical personnel are increasingly demanding for technologies (possibly low-cost) to quantitatively measure and assess patients’ improvements during rehabilitation exercises. In this paper, we focus the attention on the assessment of rehabilitation process for injured shoulders. This is particularly challenging because the recognition and the measurement of compensatory movements are very difficult during visual assessment and the movements of a shoulder are complex and arduous to be captured. The proposed solution integrates a low-cost Mocap system with video processing techniques to allow a quantitative evaluation of abduction, which is one of the first post-surgery exercises required for shoulder rehabilitation. The procedure is based on a set of open-source software tools to measure abduction and evaluate the correctness of the movement by detecting and measuring compensatory movements according to the parameters commonly considered by the physicians. Finally, a preliminary results and future works are presented and discussed.

Keywords: Embedded Knowledge | Medical assessment | Microsoft Kinect v2 | Motion Capture | Post-surgery shoulder

Abstract: Dynamic characterization of vibrating targets represents a critical issue for many industrial fields. In this paper, a stereo-camera system integrated with a Digital Image Correlation (DIC) algorithm is proposed with the aim at performing 3D full-field vibration measurements in the range of kHz. The system exploits two industrial low-speed cameras, and the Nyquist-Shannon frequency limitation is overcome by a down-sampling approach under the hypothesis that the vibration signal is characterized by a single known frequency component. Experimental results obtained from the measurement of vibrational responses of a cantilever plate excited at three high-frequency resonance values (1121 Hz, 2956 Hz and 4010 Hz) are provided. A comparison with numerical analyses evidences the effectiveness of the proposed approach.

Keywords: Digital Image Correlation | Low-frame-rate cameras | Stereo-camera setup | Vibration measurement

Abstract: In recent decades, increasing attention is being paid to the multidisciplinary approach that allows the performance of both a preventive conservation and a more invasive restoration action. In this context, the present study aims to acquire information and data from field surveys undertaken in San Domenico Church, Southern Calabria, in order to provide a tool for the recording and the inventory of damage and decay phenomena, and assess their causes and scale. The subsequent calculation of damage indices also provided useful information in order to allow the prioritization of conservation and preservation responses.

Keywords: Built heritage | Calabria | Computer graphics | Damage diagnosis | Decay | Italy | Photogrammetry

Abstract: The paper presents the MOLUX project which aims to design and develop a system capable of supporting the underwater operators by means of innovative technologies for the diagnosis, recovery, management, conservation, and valorization of the archaeological and naturalistic assets in the marine environment. This system allows to increase the efficiency and the safety of the operations carried out in the underwater environment thanks to its capabilities: to make the diver aware of his/her position; to acquire geolocated data (images, videos, notes, environmental parameters); to optimize and monitor the planned dive route.

Keywords: Autonomous surface vehicle | Diver operation support | Monitoring | Underwater localization | Underwater tablet

Abstract: Histological evaluation plays a major role in cancer diagnosis and treatment. The appearance of H&E-stained images can vary significantly as a consequence of differences in several factors, such as reagents, staining conditions, preparation procedure and image acquisition system. Such potential sources of noise can all have negative effects on computer-assisted classification. To minimize such artefacts and their potentially negative effects several color pre-processing methods have been proposed in the literature—for instance, color augmentation, color constancy, color deconvolution and color transfer. Still, little work has been done to investigate the efficacy of these methods on a quantitative basis. In this paper, we evaluated the effects of color constancy, deconvolution and transfer on automated classification of H&E-stained images representing different types of cancers—specifically breast, prostate, colorectal cancer and malignant lymphoma. Our results indicate that in most cases color pre-processing does not improve the classification accuracy, especially when coupled with color-based image descriptors. Some pre-processing methods, however, can be beneficial when used with some texture-based methods like Gabor filters and Local Binary Patterns.

Keywords: Color | H&E staining | Histology images | Texture

Abstract: In this paper, we investigate the role of shape and texture features from 18F-FDG PET/CT to discriminate between benign and malignant solitary pulmonary nodules. To this end, we retrospectively evaluated cross-sectional data from 111 patients (64 males, 47 females, age = 67.5 ± 11.0) all with histologically confirmed benign (n = 39) or malignant (n = 72) solitary pulmonary nodules. Eighteen three-dimensional imaging features, including conventional, texture, and shape features from PET and CT were tested for significant differences (Wilcoxon-Mann-Withney) between the benign and malignant groups. Prediction models based on different feature sets and three classification strategies (Classification Tree, k-Nearest Neighbours, and Naïve Bayes) were also evaluated to assess the potential benefit of shape and texture features compared with conventional imaging features alone. Eight features from CT and 15 from PET were significantly different between the benign and malignant groups. Adding shape and texture features increased the performance of both the CT-based and PET-based prediction models with overall accuracy gain being 3.4–11.2 pp and 2.2–10.2 pp, respectively. In conclusion, we found that shape and texture features from 18F-FDG PET/CT can lead to a better discrimination between benign and malignant lung nodules by increasing the accuracy of the prediction models by an appreciable margin.

Keywords: Radiomics | Shape | Solitary pulmonary nodule | Texture

Abstract: There is increasing evidence that shape and texture descriptors from imaging data could be used as image biomarkers for computer-assisted diagnosis and prognostication in a number of clinical conditions. It is believed that such quantitative features may help uncover patterns that would otherwise go unnoticed to the human eye, this way offering significant advantages against traditional visual interpretation. The objective of this paper is to provide an overview of the steps involved in the process – from image acquisition to feature extraction and classification. A significant part of the work deals with the description of the most common texture and shape features used in the literature; overall issues, perspectives and directions for future research are also discussed.

Keywords: Computer-assisted medicine | Radiomics | Shape | Texture

Abstract: Cellular materials have a bulk matrix with a larger number of voids named also cells. Metallic foams made by powder technology represent stochastic closed cells. The related inhomogeneity leads to a scattering of results both in terms of stress-strain curves and maximum strength. Scattering is attributed to relative density variations and local cell discontinuities and it is confirmed also in case of dynamic loading. Finite element simulations through geometrical models that are able to capture the void morphology (named “mesoscale models”), confirm these results and some efforts have been already done to quantify the relationship between shape irregularities and mechanical behavior. The aim of this paper is to present the dynamic characterization of an AA7075 closed cell material and to calibrate its mesoscale finite element model according to the related cell shape distribution. Specimens have been derived from a small ingot (45x45x100 mm) divided along sections so that morphological analysis and experimental tests have been carried out. Specimens extracted from a half of the ingot have been used for dynamic compression tests by means of a split Hopkinson bar, meanwhile specimens extracted from the other half of the ingot have been dissected for porosity distribution analyses carried out by means of image analysis. Stress-strain curves obtained from the mechanical tests have been discussed in terms of strain rate and statistical descriptors of the porosity. Successively a 3D-model of the specimen has been generated starting from the Voronoi algorithm, assigning as input the above-mentioned statistical distribution of the porosity. Due to the peculiarity of the cell morphology (e.g. single larger cells), stress-strain localization has been demonstrated as one of the reasons of the scattering found during the experiments. A material model, to reproduce the investigated foam mechanical behavior, has been calibrated. Despite the difference among experiments the material model is able to reproduce all of them. Difference between the model coefficients quantifies roughly the difference due to the local geometry of the cells.

Keywords: Aluminum foams | Image analysis | Impact test | Porosity distribution | Strain rate effect | Voronoi model

Abstract: The introduction of the vacuum bell (VB) for the conservative treatment of Pectus Excavatum (PE) has led to a new non-invasive alternative to thoracic surgery. The VB works by elevating the chest as long as a negative differential pressure is internally assured. In recent years studies have been conducted to validate this type of treatment and to outline its correct use; results show a short-term PE improvement when the device is worn for a minimum of 30 min (twice a day) up to a maximum of several hours a day for 12–15 months. Although the worldwide diffusion of VB devices increases year after year, its ability to lift the chest during treatment with respect to the applied pressure has begun to be evaluated only recently. In this paper, a new instrument for measuring chest elevation during treatment is presented and validated. The proposed system consists of two measurement devices: a commercial instrument for the detection of the negative pressure inside the VB, and a specifically developed optical system for the detection of chest movement. The effectiveness of the proposed system, tested on five paediatric patients, paves the way to the objective definition of an optimised patient specific VB scheme of use.

Keywords: Image processing | Optical measurement | Pectus Excavatum | Vacuum bell

Abstract: Additive Manufacturing is becoming a suitable production process for many industries: it is based on the idea of adding material layer by layer, in opposite to traditional manufacturing processes. This technology shows advantages as design flexibility, internal logistics minimization and product customization that make it perfect to produce customized parts and all the applications where low production rates occur. The production of spare parts for classic or luxury cars is a field where Additive Manufacturing can be adopted because of low demand and relevant costs to manage stocks keeping several different parts in the after-sales inventory. The photogrammetry technique has been investigated to obtain the 3D model of the component to be replaced and send it to decentralized production centers equipped with 3D printers. This approach can enhance by far the supply chain management for automotive spare parts.

Keywords: Additive Manufacturing | Automotive | Maintenance | Photogrammetry | Supply chain management

Abstract: Nowadays, the development of Internet of Things (IoT) technologies have been enhancing the factory digitalization with several advantages in terms of production efficiency, product quality, and cost reduction. This opportunity encourages the implementation of digital twins related to physical systems for controlling the production workflow in real time. Firstly, the paper studies the enabling technologies for supporting the defect analysis in the context of Industry 4.0 for mechanical workpieces. Secondly, the approach aims to study the integration between the CAD geometry and the quality check process for the inspection planning. A Knowledge-Based tool has been proposed to support the configurations of the quality control chain for each CAD geometry. The test case is focused on the fragmented production of customized gearbox parts.

Keywords: Gearbox | Industry 4.0 | Knowledge Base | Machine Vision | Quality Control

Abstract: Background: Lumbrical muscles originate in the palm from the 4 tendons of the flexor digitorum profundus and course distally along the radial side of the corresponding metacarpophalangeal joints, in front of the deep transverse metacarpal ligament. The first and second lumbrical muscles are typically innervated by the median nerve, and third and fourth by the ulnar nerve. A plethora of lumbrical muscle variants has been described, ranging from muscles’ absence to reduction in their number or presence of accessory slips. The current cadaveric study highlights typical and variable neural supply of lumbrical muscles. Materials: Eight (3 right and 5 left) fresh frozen cadaveric hands of 3 males and 5 females of unknown age were dissected. From the palmar wrist crease, the median and ulnar nerve followed distally to their terminal branches. The ulnar nerve deep branch was dissected and lumbrical muscle innervation patterns were noted. Results: The frequency of typical innervations of lumbrical muscles is confirmed. The second lumbrical nerve had a double composition from both the median and ulnar nerves, in 12.5% of the hands. The thickest branch (1.38 mm) originated from the ulnar nerve and supplied the third lumbrical muscle, and the thinnest one (0.67 mm) from the ulnar nerve and supplied the fourth lumbrical muscle. In 54.5%, lumbrical nerve bifurcation was identified. Conclusion: The complex innervation pattern and the peculiar anatomy of branching to different thirds of the muscle bellies are pointed out. These findings are important in dealing with complex and deep injuries in the palmar region, including transmetacarpal amputations.

Keywords: anomaly | clinical implication | lumbrical muscle | lumbrical nerve | variation

Abstract: In the field of Engineering, research has conveniently exploited the fluids for energy production. The possibility to use marine renewable energy is still under development, in particular, among the wave energy converter devices the U-OWC systems are the most promising. The main objective of this work is to validate a numerical model with an experimental campaign that aims to simulate the flow field in front of the breakwater and inside the U-OWC. The tests were carried out to understand the hydrodynamic behaviour of the device in regular wave conditions, inside a flume with rectangular section, equipped by a piston-type wave-maker and a U-OWC device, reproducing the REWEC caisson installed in the Natural Ocean Engineering Laboratory (NOEL) of Reggio Calabria, with a 1:13.5 scale. Measurements of the water free surface were used exclusively to validate the 2D numerical model developed through the Ansys Fluent Computational Fluid-Dynamics (CFD) Software. The numerical model solves the fluid flow field using the RANS equations, in which the air-water interaction governed by this set of partial difference equations is solved with the Finite Volume Method (FVM). In conclusion, results related to the energy efficiency of the caisson were extrapolated from the validated numerical model.

Keywords: Computational fluid dynamics | Image analysis | U-OWC | Wave energy

Abstract: Pectus Excavatum (PE) is a congenital anomaly of the ribcage, at the level of the sterno-costal plane, which consists of an inward angle of the sternum, in the direction of the spine. PE is the most common of all thoracic malformations, with an incidence of 1 in 300-400 people. To monitor the progress of the pathology, severity indices, or thoracic indices, have been used over the years. Among these indices, recent studies focus on the calculation of optical measures, calculated on the optical scan of the patient's chest, which can be very accurate without exposing the patient to invasive treatments such as CT scans. In this work, data from a sample of PE patients and corresponding doctors' severity assessments have been collected and used to create a decision tool to automatically assign a severity value to the patient. The idea is to provide the physician with an objective and easy to use measuring instrument that can be exploited in an outpatient clinic context. Among several classification tools, a Probabilistic Neural Network was chosen for this task for its simple structure and learning mode.

Abstract: Pectus Excavatum (PE) is a congenital anomaly of the thoracic cage, at the level of the sternal-costal plane, which consists of an inward angle of the sternum, in the direction of the spine. Its incidence, equal to 1 in 300–400 people, makes it the most frequent among thoracic malformations. For a proper care of patients suffering from PE, it is essential to monitor the progression of the disease and estimate its severity, in order to follow the course of the pathology over time and define the correct treatment. To this end, over the years, severity indexes, or chest indexes, have been introduced. Among them, in recent years, the so-called optical indices, calculated on optical scans of the patient’s chest, are gaining ground. In fact, the optical scan is faster to apply and prevents the patient from being exposed to radiation. In this work the peculiar morphological features of PE have been examined by extracting various geometric parameters, in order to develop an outpatient support tool for the evaluation of the severity of the pathology and the monitoring of its progression over time. The extracted values have been compared against a ground truth obtained through five independent surveys collected from paediatric specialists. A Linear Discriminant Analysis was performed to determine the accuracy of the classification using the proposed geometric parameters, obtaining positive results.

Keywords: Clinical support | Depth camera | Pectus Excavatum | Severity index

Abstract: The most common clinical treatment for ear deformities or non-congenital abnormalities is the reconstruction of the missing geometry using autologous costal cartilage. The surgical procedure consists in cutting, sculpting and suturing harvested costal cartilage from the patient to recreate an ear shape which is symmetric to the contralateral ear. During chirurgical operation, surgeons needs an accurate 3D template as reference to reproduce the ear. For this purpose, reverse engineering and additive manufacturing techniques can be employed. Specifically, this works aims to develop a reliable, low-cost and user-friendly system, to acquire the healthy ear geometry in clinical environment avoiding head patient’s exposition to radiation (MRI, CT scan). An ideal acquisition setup and device have been selected to achieve accurate results. To this end, a casted model of an ear was created as reference, and the best setup was evaluated by comparing the obtained 3D reconstructions with it. Once the setup has been determined, the anatomies of five volunteers were acquired, to test the methodology on human subjects.

Keywords: 3D model | Ear | Microtia | Photogrammetry | RealSense D415

Abstract: The paper describes the conceptual model of an emotion-aware car interface able to: map both the driver’s cognitive and emotional states with the vehicle dynamics; adapt the level of automation or support the decision-making process if emotions negatively affecting the driving performance are detected; ensure emotion regulation and provide a unique user experience creating a more engaging atmosphere (e.g. music, LED lighting) in the car cabin. To enable emotion detection, it implements a low-cost emotion recognition able to recognize Ekman’s universal emotions by analyzing the driver’s facial expression from stream video. A preliminary test was conducted in order to determine the effectiveness of the proposed emotion recognition system in a driving context. Results evidenced that the proposed system is capable to correctly qualify the drivers’ emotion in a driving simulation context.

Keywords: Driver Monitoring System | Emotion recognition | Facial expression recognition

Abstract: Advanced Driver-Assistance Systems (ADASs) are used for increasing safety in the automotive domain, yet current ADASs notably operate without taking into account drivers’ states, e.g., whether she/he is emotionally apt to drive. In this paper, we first review the state-of-the-art of emotional and cognitive analysis for ADAS: We consider psychological models, the sensors needed for capturing physiological signals, and the typical algorithms used for human emotion classification. Our investigation highlights a lack of advanced Driver Monitoring Systems (DMSs) for ADASs, which could increase driving quality and security for both drivers and passengers. We then provide our view on a novel perception architecture for driver monitoring, built around the concept of Driver Complex State (DCS). DCS relies on multiple non-obtrusive sensors and Artificial Intelligence (AI) for uncovering the driver state and uses it to implement innovative Human-Machine Interface (HMI) functionalities. This concept will be implemented and validated in the recently EU-funded NextPerception project, which is briefly introduced.

Keywords: Advanced Driver-Assistance System (ADAS) | Artificial Intelligence (AI) | Driver Complex State (DCS) | Driver safety and comfort | Emotion recognition

Abstract: This paper introduces a motion analysis system based on a network of common RGB cameras, which provides the measurement of various angles considered for postural assessment, in order to facilitate the evaluation of the ergonomic indices commonly used for the determination of risk of musculoskeletal disorders of operators in manufacturing workplaces. To enable the tracking of operator postures during the performed tasks, the system exploits the multi person keypoints detection library “OpenPose”. The proposed system has been validated with a real industrial case study regarding a washing machine assembly line. Results suggest how the proposed system supports ergonomists in risk assessment of musculoskeletal disorders through the OCRA index.

Keywords: Assembly line | Ergonomic assessment | Manufacturing | Motion capture | OCRA index | Posture analysis

Abstract: Vitiligo vulgaris is an autoimmune disease which causes a strong reduction of the cells producing melanin, which is the main skin pigment. This results in the growth of white patches on patients' skin, which are more or less visible, depending on the skin phototype. Precise, objective and fast detection of vitiligo patches would be crucial to produce statistically relevant data on huge populations, thus giving an insight on the disease. However, few methods are available in literature. In the present paper, a semi-automatic tool based on image processing to detect facial vitiligo patches is described. The tool requires pictures to be captured under black light illumination, which enhances patches contrast with respect to healthy skin. The user is only required to roughly define the regions of interest and set a global threshold, thus, no specific image-processing skills are required. An adaptive algorithm then automatically discerns between vitiligo and healthy skin pixels. The tools also allow for a statistical data interpretation by overlapping the detected patches of all patients on a face template through an occurrence map. Preliminary results obtained on a small population of 15 patients allowed us to assess the tool's performance. Patch detection was checked by an experienced dermatologist, who confirmed the detection for all the studied patients, thus supporting the effectiveness of the proposed tool.

Keywords: Black light | Image processing | Semi-automatic vitiligo detection | Vitiligo

Abstract: The aim of this study was to confirm the identities of numerous portraits attributed to the composer Vincenzo Bellini by using 3D-to-2D projection. This study also followed on from earlier research on three death masks of Bellini, the results of which had shown that the wax mask in Catania's Bellini museum best represented Bellini's face compared to the other two. This study used the aforementioned 3D wax death mask obtained through Reverse Engineering as a reference for a morphometric comparison with 14 other portraits. For each portrait, the linear 3D-to-2D transformation M was found which minimized the distance between the 2D landmarks in the picture and the projected landmarks on the 3D mask. This normalized the distances considering the scale of the portrait and the final dissimilarity score with the mask. In particular, the analytical results were able to identify two portraits which particularly resembled the 3D death mask providing future researchers with the chance to carry out historical-artistic evaluations. We were also able to develop a new tool – Image Mark Pro - to easily annotate 2D images by introducing landmark locations. Since it was so reliable for manually annotating landmarks, we decided to make it publicly available for future research.

Keywords: 3D death mask | 3D-2D comparison | Face recognition | Landmarks projection

Abstract: The current research reports for the first time the use of blends of poly(ε-caprolactone) (PCL) and poly(ester amide) (PEA) for the fabrication of 3D additive manufactured scaffolds. Tailor made PEA was synthesized to afford fully miscible blends of PCL and PEA using different percentages (5, 10, 15 and 20% w/w). Stability, characteristic temperatures and material's compatibility were studied through thermal analyses (i.e., TGA, DSC). Even though DMTA and static compression tests demonstrated the possibility to improve the storage modulus, Young's modulus and maximum stress by increasing the amount of PEA, a decrease of hardness was found beyond a threshold concentration of PEA as the lowest values were achieved for PCL/PEA (20% w/w) scaffolds (from 0.39 ± 0.03 GPa to 0.21 ± 0.02 GPa in the analysed load range). The scaffolds presented a controlled morphology and a fully interconnected network of internal channels. The water contact angle measurements showed a clear increase of hydrophilicity resulting from the addition of PEA. This result was further corroborated with the improved adhesion and proliferation of human mesenchymal stem cells (hMSCs). The presence of PEA also influenced the cell morphology. Better cell spreading and a much higher and homogenous number of cells were observed for PCL/PEA scaffolds when compared to PCL ones.

Keywords: Additive manufacturing | Biological properties | Image analysis | Poly(ester amide) | Scaffold design | Thermal and mechanical properties

Abstract: The control of the process–structure–property relationship of a material plays an important role in the design of biomedical metal devices featuring desired properties. In the field of endodontics, several post-core systems have been considered, which include a wide range of industrially developed posts. Endodontists generally use posts characterized by different materials, sizes, and shapes. Computer-aided design (CAD) and finite element (FE) analysis were taken into account to provide further insight into the effect of the material–shape combination of metal posts on the mechanical behavior of endodontically treated anterior teeth. In particular, theoretical designs of metal posts with two different shapes (conical-tapered and conical-cylindrical) and consisting of materials with Young’s moduli of 110 GPa and 200 GPa were proposed. A load of 100 N was applied on the palatal surface of the crown at 45◦ to the longitudinal axis of the tooth. Linear static analyses were performed with a non-failure condition. The results suggested the possibility to tailor the stress distribution along the metal posts and at the interface between the post and the surrounding structures, benefiting from an appropriate combination of a CAD-based approach and material selection. The obtained results could help to design metal posts that minimize stress concentrations.

Keywords: Computer-aided design (CAD) | Dental materials | Finite element analysis | Image analysis | Mechanical properties | Metal posts

Abstract: This paper deals with parenthood perception (maternal and paternal) after the visualization and interaction (touch) with a 3D printed facial fetal model. The model is created using Additive Manufacturing techniques, starting from the image elaboration of routine ultrasound data. In this study, the method used for the elaboration and construction of 3D printable models of fetal faces starting from routine ultrasound images is briefly described. In addition, we present the results of a new survey conducted with future parents at the Altamedica clinic (Rome, Italy) to verify whether there are any benefits derived from the use of 3D printing models with future parents, both regarding the improvement of the parenthood experience, and the improvement of the understanding and collaboration with the physicians in case of fetal malformations, using 3D models coupled with the data of routine ultrasound examinations.

Keywords: 3D ultrasound | Additive manufacturing | Fetal face | Image processing | Parenthood perception | Survey

Abstract: The use of fast and accurate scanning systems for human body digitization might pave the way towards the development of less invasive processes for medical manufacturing. In this work, an advanced measurement system for human body 3D reconstruction is used to design tailored assistive devices. The system is a photogrammetric 3D body scanner developed by the authors.

Keywords: 3D body measurements | assistive devices | medical manufacturing

Abstract: Introduction and Objectives Fabrication processes for spinal orthoses require accurate three-dimensional (3D) models of the patients' trunk. Current methods for 3D reconstruction used in this field mainly include laser or structured light scanning; these methods are time expensive and invasive, especially for patients with partial disabilities. Therefore, a theoretically instant system for data acquisition of anatomical structure is highly desirable. The objective of this work is to show the feasibility of using digital photogrammetry for human body digitization to generate accurate 3D models of the patients' trunk for spinal orthoses fabrication. Materials and Methods Multiple synchronized two-dimensional images of the human torso are captured from different points of view using a photogrammetric scanner. A 3D model is generated using the state-of-the-art algorithms for point cloud and surface reconstruction. The digitized model is then used as input for the standard computer-aided design (CAD)/computer-aided manufacturing (CAM) process of fabrication. R4D from Rodin4D is used as prosthetics and orthotics CAD software. A robotic cell constituted by a six-axis KUKA KR 30-3 is used for milling a polyurethane foam. Vacuum forming is then adopted to generate the orthosis. Two spinal orthoses are fabricated using this approach and a classical one; then, they are evaluated using quantitative and qualitative metrics. Results The data acquisition using this approach lasts 50 milliseconds. The 3D reconstruction accuracy averages 0.21 ± 1.27 mm, which suits for the considered health care scenario. Results of the initial fitting of the orthoses fabricated with the presented method show better performances in terms of time (44%), product quality (35%), and patient experience (30%). Conclusions Digital photogrammetry can be used to enhance the data acquisition and data processing of anatomical surfaces for the CAD/CAM process of spinal orthoses. The data acquisition time, almost instant, allows an easy compliance of many patients. The data processing allows generating accurate models of the patient's body. The overall process generates orthoses with a better quality with respect to those manufactured using conventional procedures. ©

Keywords: CAD/CAM | fabrication techniques | photogrammetry | prosthetics and orthotics | spinal orthoses | three-dimensional reconstruction

Abstract: A single-camera stereo-digital image correlation (stereo-DIC) system to obtain 3D full-field vibration measurements is proposed. The optical setup is composed of two planar mirrors and a single low frame rate camera, thus resulting in a compact and low-cost equipment. The two mirrors are used to create pseudo-stereo images of a target surface on the camera sensor, which are then correlated by using stereo-DIC. The image acquisition process is carried out at low frame rates and the Nyquist-Shannon frequency limitation is overcome by adopting a down-sampling approach under the hypothesis that the vibration signal is characterized by a single known frequency component. The developed pseudo-stereo DIC system allows to obtain 3D full-field vibration measurements in a frequency range up to 4 kHz even with an available frame rate (at full resolution) of 178 fps. The effectiveness of the described approach has been verified by performing vibration measurements on a cantilever plate and a turbine blade.

Keywords: Digital image correlation | Down-sampling approach | Single low-speed camera | Vibration measurement

Abstract: The concept of "surface modeling" generally describes the process of representing a physical or artificial surface by a geometric model, namely a mathematical expression. Among the existing techniques applied for the characterization of a surface, terrain modeling relates to the representation of the natural surface of the Earth. Cartographic terrain or relief models as threedimensional representations of a part of the Earth's surface convey an immediate and direct impression of a landscape and are much easier to understand than two-dimensional models. This paper addresses a major problem in complex surface modeling and evaluation consisting in the characterization of their topography and comparison among different textures, which can be relevant in different areas of research. A new algorithm is presented that allows calculating the fractal dimension of images of complex surfaces. The method is used to characterize different surfaces and compare their characteristics. The proposed new mathematical method computes the fractal dimension of the 3D space with the average space component of Hurst exponent H, while the estimated fractal dimension is used to evaluate, compare and characterize complex surfaces that are relevant in different areas of research. Various surfaces with both methods were analyzed and the results were compared. The study confirms that with known coordinates of a surface, it is possible to describe its complex structure. The estimated fractal dimension is proved to be an ideal tool for measuring the complexity of the various surfaces considered.

Keywords: Fractal dimension | Hurst exponent H | Image analysis | Space component | Surface

Abstract: This paper compares the effects of colour pre-processing on the classification performance of H&E-stained images. Variations in the tissue preparation procedures, acquisition systems, stain conditions and reagents are all source of artifacts that can affect negatively computer-based classification. Pre-processing methods such as colour constancy, transfer and deconvolution have been proposed to compensate the artifacts. In this paper we compare quantitatively the combined effect of six colour pre-processing procedures and 12 colour texture descriptors on patch-based classification of H&E-stained images. We found that colour pre-processing had negative effects on accuracy in most cases – particularly when used with colour descriptors. However, some pre-processing procedures proved beneficial when employed in conjunction with classic texture descriptors such as co-occurrence matrices, Gabor filters and Local Binary Patterns.

Keywords: Colour | Eosin | Hematoxylin | Histology | Texture

Abstract: In this paper we investigate extensions of Local Binary Patterns (LBP), Improved Local Binary Patterns (ILBP) and Extended Local Binary Patterns (ELBP) to colour textures via two different strategies: intra-/inter-channel features and colour orderings. We experimentally evaluate the proposed methods over 15 datasets of general and biomedical colour textures. Intra- and inter-channel features from the RGB space emerged as the best descriptors and we found that the best accuracy was achieved by combining multi-resolution intra-channel features with single-resolution inter-channel features.

Keywords: Colour | Local binary patterns | Texture

Abstract: Wear and rolling contact fatigue are competing phenomena in railway wheels, as wear tends to shorten or remove surface cracks nucleated by ratcheting. The presence of water at the contact interface can enhance crack propagation leading to fatigue failure. This topic was studied taking advantage of innovative measurement systems developed for assessing the damage in bi-disc rolling contact tests, including a vision system for the acquisition and elaboration of surface images and a machine-learning technique for vibration measurement and analysis. Tests of different total duration with alternated dry and wet contact phases were carried out. The analysis of the collected measurements allowed identifying when crack propagation begins to prevail on wear: this occurred well earlier than the visible emergence of fatigue damage. If short dry and wet contact sessions are alternated, the onset of fluid driven crack propagation is delayed, because initially the dry sessions are not long enough to allow surface cracks to form by ratcheting, and in the subsequent wet session ratcheting is suspended due to low friction. If the alternated dry-wet contact sessions are longer, the onset of fluid driven crack propagation is accelerated, as in the dry sessions ratcheting proceeds more forming longer surface cracks, which are able to propagate in the subsequent wet phase.

Keywords: Crack propagation | Dry-wet contact | Ratcheting | Vibration analysis | Vision systems | Wheel steel

Abstract: The paper describes the design of a wearable and wireless system that allows the real-time identification of some gestures performed by basketball players. This system is specifically designed as a support for coaches to track the activity of two or more players simultaneously. Each wearable device is composed of two separate units, positioned on the wrists of the user, connected to a personal computer (PC) via Bluetooth. Each unit comprises a triaxial accelerometer and gyroscope, a microcontroller, installed on a TinyDuino platform, and a battery. The concept of activity recognition chain is investigated and used as a reference for the gesture recognition process. A sliding window allows the system to extract relevant features from the incoming data streams: mean values, standard deviations, maximum values, minimum values, energy, and correlations between homologous axes are calculated to identify and differentiate the performed actions. Machine learning algorithms are implemented to handle the recognition phase.

Abstract: Structural S355 steel is widely applied in various sectors. Fatigue properties are of fundamental importance and extremely time consuming to be assessed. The aim of this research activity is to apply the Static Thermographic Method during tensile tests and correlate the temperature trend to the fatigue properties of the same steel. The Digital Image Correlation (DIC) and Infrared Thermography (IR) techniques have been used during all static tests. The Digital Image Correlation technique allowed the detection of displacements and strain, and so the evaluation of the mechanical properties of the material. Traditional fatigue tests were also performed in order to evaluate the stress-number of cycles to failure curve of the same steel. The value of the fatigue limit, obtained by the traditional procedure, was compared with the values predicted by means of the Static Thermographic Method (STM) obtained from tensile tests. The predicted values are in good agreement with the experimental values of fatigue life.

Keywords: Digital image correlation | Fatigue | Infrared thermography | Marine structures | Tensile tests

Abstract: Background Preclinical training in perforator flap harvesting is typically conducted on living animal models; however, repeated training is not possible with these models because of ethical and/or economical constraints. We describe an anterolateral thigh flap (ALT flap) training model using chicken thigh that seems to be an appropriate training model prior, for example, to raise a perforator flap in a living rat or swine model. Methods A total of 10 chicken legs were used in this study. Six chicken legs were anatomically dissected to confirm the presence of the perforator and to identify the main vascular tree. In four chicken legs, a skin flap was planned based on the perforator and intramuscular dissection was performed under magnification. Results The perforator was identified in all dissections and was consistently found 3 cm above the line extending from the patella to the head of the femur in its third proximal. Proximally, the mean diameter of the artery and vein was 0.56 (σ = 0.04) and 0.84 (σ = 0.06) mm, respectively. The mean dissection time to raise the flap was 88 (σ = 7) min. Conclusion This is the first description of a nonliving biological simulation model for training in perforator flap dissection that mimics an ALT flap. As an ex vivo chicken model, it is a cost effective and readily accessible model suitable for repeated practice.

Keywords: ALT | chicken | perforator flap | training

Abstract: In the fashion field, the use of electroplated small metal parts such as studs, clips and buckles is widespread. The plate is often made of precious metal, such as gold or platinum. Due to the high cost of these materials, it is strategically relevant and of primary importance for manufacturers to avoid any waste by depositing only the strictly necessary amount of material. To this aim, companies need to be aware of the overall number of items to be electroplated so that it is possible to properly set the parameters driving the galvanic process. Accordingly, the present paper describes a simple, yet effective machine vision-based method able to automatically count small metal parts arranged on a galvanic frame. The devised method, which relies on the definition of a rear projection-based acquisition system and on the development of image processing-based routines, is able to properly count the number of items on the galvanic frame. The system is implemented on a counting machine, which is meant to be adopted in the galvanic industrial practice to properly define a suitable set or working parameters (such as the current, voltage, and deposition time) for the electroplating machine and, thereby, assure the desired plate thickness from one side and avoid material waste on the other.

Keywords: Electro-deposition industry | Image analysis | Item counting device | Machine vision

Abstract: This paper presents a software based on an innovative Convolutional Neural Network model to recognize the six Ekman's universal emotions from the photos of human faces captured in the wild. The CNN was trained using three different datasets already labeled and merged after making them homogeneous. A comparison among different types of CNN architectures using the Keras framework for Python language is proposed and the evaluation results are presented.

Keywords: convolutional neural network | deep learning | emotion recognition

Abstract: The study of human factors is fundamental for the human-centered design of Smart Workplaces. IIoT (Industrial Internet of Things) technologies, mainly wearable devices, are becoming necessary to acquire data, whose analysis will be used to make decision in a smart way. For industrial applications, motion-tracking systems are strongly developing, being not invasive and able to acquire high amounts of data related to human motion in order to evaluate the ergonomic indexes in an objective way, as well as suggested by standards. For these reasons, a modular inertial motion capture system has been developed at the Department of Engineering of the University of Campania Luigi Vanvitelli. By using low cost Inertial Measurement Units – IMU and sensor fusion algorithms based on Extended Kalman filtering, the system is able to estimate the orientation of each body segment, the posture angles trends and the gait recognition during a working activity in industrial environment. From acquired data it is possible to develop further algorithms to online asses ergonomic indexes according to methods suggested by international standards (i.e. EAWS, OCRA, OWAS). In this paper, the overall ergonomic assessment tool is presented, with an extensive result campaign in automotive assembly lines of Fiat Chrysler Automobiles to prove the effectiveness of the system in an industrial scenario.

Keywords: IMU | Industrial environment | Industrial ergonomics | Motion capture | Wearable device

Abstract: Nowadays, facial mimicry studies have acquired a great importance in the clinical domain and 3D motion capture systems are becoming valid tools for analysing facial muscles movements, thanks to the remarkable developments achieved in the 1990s. However, the face analysis domain suffers from a lack of valid motion capture protocol, due to the complexity of the human face. Indeed, a framework for defining the optimal marker set layout does not exist yet and, up to date, researchers still use their traditional facial point sets with manually allocated markers. Therefore, the study proposes an automatic approach to compute a minimum optimized marker layout to be exploited in facial motion capture, able to simplify the marker allocation without decreasing the significance level. Specifically, the algorithm identifies the optimal facial marker layouts selecting the subsets of linear distances among markers that allow to automatically recognizing with the highest performances, through a k-nearest neighbours classification technique, the acted facial movements. The marker layouts are extracted from them. Various validation and testing phases have demonstrated the accuracy, robustness and usefulness of the custom approach.

Keywords: 3D face | Face analysis | Feature extraction | Marker optimization | Motion capture

Abstract: This paper describes the conceptual model and the implementation of an emotion aware system able to manage multimedia contents (i.e., music tracks) and lightning scenarios, based on the user’s emotion, detected from facial expressions. The system captures the emotions from the user’s face expressions, mapping them into a 2D valence-arousal space where the multimedia content is mapped and matches them with lighting color. A preliminary experimentation involved a total of 26 subjects has been carried out with the purpose of assess the system emotion recognition effectiveness and its ability to manage the environment appropriately. Results evidenced several limits of emotion recognition through face expressions detection and opens to several research challenges.

Keywords: Affective computing | Ambient intelligence | Emotion detection | Emotion recognition | Emotion-aware system | Face expression recognition | Smart environment

Abstract: Aboveground biomass (AGB) is a parameter commonly used for assessing and monitoring primary productivity of grassland communities. Destructive AGB measurements, although accurate, are time-consuming and do not allow for repeated measurements as required by monitoring protocols. Structure-from-motion (SfM) photogrammetry has been proved to be a reliable tool for rapid and not destructive AGB estimations in grass systems. Three-dimensional (3D) models of fourteen 1 × 1 m2 pasture plots were reconstructed and AGB volume measured under several measurement settings. Volume-based AGB measures were regressed to AGB values resulting from destructive methods to identify the measurement settings that show the best fit. Furthermore, 3D models of four mountain pasture plots were reconstructed in May, July, and August. Models relative to the same plot were aligned and their relative difference measured to produce a diachronic canopy variation model (DCVM). On the measured volume (Vd), the coefficient of density (cρ) was applied to adjust the volume values (Vadj) in relation to variation due to different DCVM point densities. The measurement setting for AGB volume estimations strongly influenced their correlation with traditional AGB scores. The best fit was obtained selecting 1 mm grid cell size and minimum point height distance. Such options were then selected to measure the DCVM. Adjusted volumes were fully correlated with the average point distance. Three plots revealed higher rates of AGB in the spring compared to summer season, as justified by the summer aridity constraints affecting vegetation productivity in Mediterranean areas. In one plot, we found an anomalous seasonal pattern, showing an AGB reduction in spring, which can be correlated with grazing, that promoted a subsequent increment in summer. Our study indicates that image-based photogrammetric techniques allow for reliable non-destructive measurements of surface biomass in diachronic analyses, offering a valuable tool for evaluating occurrence, magnitude, and spatial patterns of variations of community primary productivity over time. Diachronic canopy variation model produced congruent patterns of inter-seasonal canopy variations proving to be a useful tool for analyzing local disturbance to vegetation canopy caused by grazing.

Keywords: biomass | coefficient of density | diachronic variation | local disturbance | non-destructive measurements | pasture community | photogrammetry | structure-from-motion

Abstract: In this paper, we present a solution for the photorealistic ambient light render of holograms into dynamic real scenes, in augmented reality applications. Based on Microsoft HoloLens, we achieved this result with an Image Base Lighting (IBL) approach. The real-time image capturing that has been designed is able to automatically locate and position directional lights providing the right illumination to the holograms. We also implemented a negative "shadow drawing" shader that contributes to the final photorealistic and immersive effect of holograms in real life. The main focus of this research was to achieve a superior photorealism through the combination of real-time lights placement and negative "shadow drawing" shader. The solution was evaluated in various Augmented Reality case studies, from classical ones (using Vuforia Toolkit) to innovative applications (using HoloLens).

Keywords: Augmented reality | Holographic shadow | Image processing | Light mapping | Rendering techniques

Abstract: The preservation status of an underwater cultural site can be determined as the combination of two primary factors, namely the site physical integrity, which results from the past and present interaction of the site itself with the biological/chemical agents located in the surrounding environment, and the exposure of the site to human-related threats. Methods to survey underwater archaeological sites have evolved considerably in the last years in order to face the challenges and problems in archaeological prospection, documentation, monitoring, and data collection.This paper presents a case-study of an archaeological documentation campaign addressed to study and monitor the preservation status of an underwater archaeological site by combining the quantitative measurements coming from optical and acoustic surveys with the study of biological colonization and bioerosion phenomena affecting ancient artefacts. In particular, we present the first results obtained in the survey and documentation campaign carried out during the spring - summer 2018 in the "Nymphaeum of Punta Epitaffio" located in the Marine Protected Area - Underwater Park of Baiae (Naples).

Keywords: 3D Imaging | 3D Mapping | Baiae Archaeological Park | Photogrammetry | Underwater Archaeology

Abstract: Objectives: To assess conceptual designs of dental posts consisting of polyetherimide (PEI) reinforced with carbon (C) and glass (G) glass fibers in endodontically treated anterior teeth. Methods: 3D tessellated CAD and geometric models of endodontically treated anterior teeth were generated from Micro-CT scan images. Model C-G/PEI composite posts with different Young's moduli were analyzed by Finite Element (FE) methods post A (57.7 GPa), post B (31.6 GPa), post C (from 57.7 to 9.0 GPa in the coronal–apical direction). A load of 50 N was applied at 45° to the longitudinal axis of the tooth, acting on the palatal surface of the crown. The maximum principal stress distribution was determined along the post and at the interface between the post and the surrounding structure. Results: Post C, with Young's modulus decreasing from 57.7 to 9.0 GPa in the coronal–apical direction, reduced the maximum principal stress distribution in the restored tooth. Post C gave reduced stress and the most uniform stress distribution with no stress concentration, compared to the other C-G/PEI composite posts. Significance: The FE analysis confirmed the ability of the functionally graded post to dissipate stress from the coronal to the apical end. Hence actual (physical) C-G/PEI posts could permit optimization of stress distributions in endodontically treated anterior teeth.

Keywords: CAD | Dental materials | Design | Endodontic treatment | Finite Element analysis | Image analysis

Abstract: Over recent years, various virtual prototyping technologies have been developed to innovate apparel industry. For each step of the garment design process one can find dedicated tools (from body acquisition to garment modelling and simulation) with the aim of making the process easier and faster. However, most of them are based on expensive solutions both for hardware and software systems. In this paper, we focus the attention on the first step of the made-to-measure garment design, i.e. customer’s measures acquisition. We present a plug-in, named Tailor Tracking, which permits to get the measurements by interacting with the customer’s avatar using hands as in the traditional way. Tailor Tracking has been developed using low cost devices, such as Microsoft Kinect sensor, Leap motion device and Oculus Rift, and open source libraries, such as Visualisation Toolkit (VTK) and Qt. The proposed approach is based on the use of multiple Kinect v2 to simultaneously acquire both customer’s body and motion. This permits to emulate the customer’s postures required to take the correct measurements. In addition, a virtual measuring tape is made available to replicate the one commonly used by the tailor. A men shirt has been considered as case study and a tailor and 14 people with no skills in garment design and different levels of experience in virtual reality technology have been involved to preliminary test Tailor tracking. Finally, tests as well as results reached so far are presented and discussed. Results have been considered quite good; however, some critical measures have been identified as well as future developments. Anyway, Tailor Tracking can represent an alternative solution to the existing approaches that automatically extract anthropometric measures from the customer’s avatar.

Keywords: Clothing design | garment measurements | hand-tracking device | head mounted display | Kinect sensors | motion capture | virtual reality

Abstract: This paper presents a novel instant 3D whole body scanner for healthcare applications. It is based on photogrammetry, a digital technology which allows to reconstruct the surface of objects starting from multiple pictures. The motivation behind this work is the development of minimally invasive procedures for instant data acquisitions of anatomical structure. The scanner provides several features of interests in 3D body scanning technologies for the healthcare domains: (i) instant capture of human body models; (ii) magnitude of accuracy in the order of 1 mm; (iii) simplicity of use; (iv) possibility to scan using different settings; (v) possibility to reconstruct the texture. The system is built upon a modular and distributed architecture. In this paper we highlight its key concepts and the methodology which has led to the current product. We illustrate its potential through one of the most promising 3D scanning healthcare applications: the data acquisition and processing of human body models for the digital manufacturing process of prostheses and orthoses. We validate the overall system in terms of conformity with the the initial requirements.

Keywords: 3D reconstruction | Body scanning | Healthcare | Human body measurements | Human body visualization | Photogrammetry | Proshetics and orthotics

Abstract: A 3D full-field optical system for high frequency vibration measurement is proposed. The system is composed of a single low-frame-rate camera and two planar mirrors. This compact optical setup overcomes the typical drawback of capturing synchronous acquisitions in the case of a camera pair. Moreover, planar mirrors allow for the use of the classical pinhole model and, thus, conventional stereo-calibration techniques. The use of a low-frame-rate camera provides on the one hand a high-resolution sensor with a relatively low-cost hardware but imposes, on the other, the adoption of a down-sampling approach, which is applicable only when a single (known) sinusoidal load is applied to the structure. The effectiveness of the proposed setup has been verified by the 3D vibration measurement of two different targets up to a frequency of 1 kHz, corresponding to a displacement amplitude of 0.01 mm.

Keywords: digital image correlation | down-sampling approach | Reverse engineering | single low-speed camera

Abstract: 3D virtual reconstruction of human body parts is nowadays a common practice in many research fields such as the medical one, the manufacturing of customized products or the creation of personal avatar for gaming purpose. The acquisition can be performed with the use of an active stereo system (i.e., laser scanner, structured light sensors) or with the use of a passive image-based approach. While the former represents a consolidated approach in human modeling, the second is still an active research field. Usually, the reconstruction of a body part through a scanning system is expensive and requests to project light on the patient’s body. On the other hand, the image-based approach could use multi-photo technique to reconstruct a real scene and provides some advantages: low equipment costs (only one camera) and rapid acquisition process of the photo set. In this work, the use of the photogrammetry approach for the reconstruction of humans’ face has been investigated as an alternative to active scanning systems. Two different photogrammetric approaches have been tested to verify their potentiality and their sensitivity to configuration parameters. An initial comparison among them has been performed, considering the overall number of points detected (sparse point cloud reconstruction, dense point cloud reconstruction). Besides, to evaluate the accuracy of the reconstruction, a set of measures used in the design of wearable head-related products has been assessed.

Abstract: Background and objective: The purpose of the present paper is to pave the road to the systematic optimization of complex craniofacial surgical intervention and to validate a design methodology for the virtual surgery and the fabrication of cranium vault custom plates. Recent advances in the field of medical imaging, image processing and additive manufacturing (AM) have led to new insights in several medical applications. The engineered combination of medical actions and 3D processing steps, foster the optimization of the intervention in terms of operative time and number of sessions needed. Complex craniofacial surgical intervention, such as for instance severe hypertelorism accompanied by skull holes, traditionally requires a first surgery to correctly “resize” the patient cranium and a second surgical session to implant a customized 3D printed prosthesis. Between the two surgical interventions, medical imaging needs to be carried out to aid the design the skull plate. Instead, this paper proposes a CAD/AM-based one-in-all design methodology allowing the surgeons to perform, in a single surgical intervention, both skull correction and implantation. Methods: A strategy envisaging a virtual/mock surgery on a CAD/AM model of the patient cranium so as to plan the surgery and to design the final shape of the cranium plaque is proposed. The procedure relies on patient imaging, 3D geometry reconstruction of the defective skull, virtual planning and mock surgery to determine the hypothetical anatomic 3D model and, finally, to skull plate design and 3D printing. Results: The methodology has been tested on a complex case study. Results demonstrate the feasibility of the proposed approach and a consistent reduction of time and overall cost of the surgery, not to mention the huge benefits on the patient that is subjected to a single surgical operation. Conclusions: Despite a number of AM-based methodologies have been proposed for designing cranial implants or to correct orbital hypertelorism, to the best of the authors’ knowledge, the present work is the first to simultaneously treat osteotomy and titanium cranium plaque.

Keywords: Additive manufacturing | CAD | Cranium surgery | Image processing

Abstract: With the aim of retrieving 3D surfaces starting from single shaded images, i.e. for solving the widely known shape from shading problem, an important class of methods is based on minimisation techniques where the expected surface to be retrieved is supposed to be coincident with the one that minimise a properly developed functional, consisting of several contributions. Despite several different contributes that can be explored to define a functional, the so called 'smoothness constraint' is a cornerstone since it is the most relevant contribute to guide the convergence of the minimisation process towards a more accurate solution. Unfortunately, in case input shaded image is characterised by areas where actual brightness changes rapidly, such a constraint introduces an undesired over-smoothing effect for the retrieved surface. The present work proposes an original strategy for avoiding such a typical over-smoothing effect, with regard to the image regions in which this is particularly undesired such as, for instance, zones where surface details are to be preserved in the reconstruction. The proposed strategy is tested against a set of case studies and compared with other traditional SFS-based methods to prove its effectiveness.

Keywords: 3D model | Minimisation | SFS | shape from shading | Smoothing | Smoothness constraint | variational approach

Abstract: Background/Aim. We retrospectively investigated the prognostic potential (correlation with overall survival) of 9 shape and 21 textural features from non-contrast-enhanced computed tomography (CT) in patients with non-small-cell lung cancer. Materials and Methods. We considered a public dataset of 203 individuals with inoperable, histologically- or cytologically-confirmed NSCLC. Three-dimensional shape and textural features from CT were computed using proprietary code and their prognostic potential evaluated through four different statistical protocols. Results. Volume and grey-level run length matrix (GLRLM) run length non-uniformity were the only two features to pass all four protocols. Both features correlated negatively with overall survival. The results also showed a strong dependence on the evaluation protocol used. Conclusion: Tumour volume and GLRLM run-length non-uniformity from CT were the best predictor of survival in patients with non-small-cell lung cancer. We did not find enough evidence to claim a relationship with survival for the other features.

Keywords: Computed tomography | Non-small-cell lung cancer | Radiomics. | Shape | Texture

Abstract: Convolutional Neural Networks have proved extremely successful in object classification applications; however, their suitability for texture analysis largely remains to be established. We investigate the use of pre-trained CNNs as texture descriptors by tapping the output of the last fully connected layer, an approach that has proved its effectiveness in other domains. Comparison with classical descriptors based on signal processing or statistics over a range of standard databases suggests that CNNs may be more effective where the intra-class variability is large. Conversely, classical approaches may be preferable where classes are well defined and homogeneous.

Keywords: Convolutional Neural Networks | Image classification | Local Binary Patterns | Texture

Abstract: In this paper, we aim at providing results concerning the application of desktop systems for rapid prototyping of medical replicas that involve complex shapes, as, for example, folds of a colon. Medical replicas may assist preoperative planning or tutoring in surgery to better understand the interaction among pathology and organs. Major goals of the paper concern with guiding the digital design workflow of the replicas and understanding their final performance, according to the requirements asked by the medics (shape accuracy, capability of seeing both inner and outer details, and support and possible interfacing with other organs). In particular, after the analysis of these requirements, we apply digital design for colon replicas, adopting two desktop systems. The experimental results confirm that the proposed preprocessing strategy is able to conduct to the manufacturing of colon replicas divided in self-supporting segments, minimizing the supports during printing. This allows also to reach an acceptable level of final quality, according to the request of having a 3D presurgery overview of the problems. These replicas are compared through reverse engineering acquisitions made by a structured-light system, to assess the achieved shape and dimensional accuracy. Final results demonstrate that low-cost desktop systems, coupled with proper strategy of preprocessing, may have shape deviation in the range of ±1 mm, good for physical manipulations during medical diagnosis and explanation.

Abstract: Finite Element Analysis (FEA) has gained an extensive application in the medical field, such as soft tissues simulations. In particular, colorectal simulations can be used to understand the interaction with the surrounding tissues, or with instruments used in surgical procedures. Although several works have been introduced considering small displacements, as a result of the forces exerted on adjacent tissues, FEA applied to colorectal surgical scenarios is still a challenge. Therefore, this work aims to provide a sensitivity analysis on three geometric models, taking in mind different bioengineering tasks. In this way, a set of simulations has been performed using three mechanical models named Linear Elastic, Hyper-Elastic with a Mooney-Rivlin material model, and Hyper-Elastic with a YEOH material model.

Keywords: Computer assisted surgical planning | Finite element analysis | Soft tissues simulation | Surface modeling

Abstract: A machine learning technique was used to monitor the state of damage of steel specimens subjected to cyclic contact fatigue tests and to make a continuous measurement without coming into contact with the specimens examined. Six different sets of specimens were considered and the torque and vibration data obtained from their respective tests were analyzed. Different statistical and spectral characteristics were obtained from each dataset, to represent their information content. The correlation existing between the characteristics was studied to select only the essential ones. The global data volume was reduced by a principal component analysis. The data thus obtained were subsequently processed, and classified, developing a K-means algorithm. The results were formulated in probabilistic terms with the aid of membership charts, confusion matrices and probability curves. The results obtained from this first analysis are highly encouraging. The algorithm is able to assess the damage status of the specimens, as well as detect the operating conditions of the machine. A substantial advantage of this method is the ability to estimate quantitatively the damage by calculating the distance of the current data from specific references. The performances of this approach were numerically estimated in terms of sensitivity, specificity and accuracy.

Abstract: Twin-disk tests are an effective method to characterize the material response to rolling sliding contact, to reproduce the damage phenomena of real components at a laboratory scale in controlled working conditions. Usually the monitoring is performed by means of “gross” parameters, such as weight loss, coefficient of friction and Barkhausen noise, and micrographs of the sample sections, at the end of the test. Visual inspection of the sample contact surface at the macro-scale yields further information about the process under analysis. In twin-disk tests, the samples are visually inspected at predetermined steps, typically by acquiring the image of their surface when the samples are stationary. The availability of a system able to capture the images of the samples while they roll during the tests is of interest to better monitor the damage evolution. In this paper, we present the results of the experiments carried out to extract quantitative information from the images captured on railway wheel samples during rolling contact tests: suitable image processing has been designed with the objective of finding meaningful, synthetic indices for the monitoring and the interpretation of the wear process, also in relation to prior knowledge about the process. The experimental work was focused on the definition of the indices, on the analysis of their behavior on different steels, and on their usefulness to predict uneven wear during the tests on the test bench.

Keywords: Damage monitoring | Image acquisition | Image processing | Twin-disk tests | Wear

Abstract: Rolling Contact Fatigue (RCF) tests are a common effective method to study the behavior of wheel- and rail-steels. The measurements usually performed are discrete and destructive: they can only be performed at each intermediate stop of a test and they result in the alteration or destruction of the examined specimens. This work aims to assess the damage level steel samples during RCF tests, making continuous, non-destructive, and contactless measurements. A machine-learning technique based on vibration and torque measurements, together with 2D image was applied to RCF-dry tests carried out on different railway wheel steels tested according to the same operating parameters. The proposed algorithm was able to quantitatively estimate the damage level of the samples by calculating the current data distance from specific references, e.g. a defined final damaged state. The used approach ensures a good degree of reliability both in terms of specificity and sensitivity.

Abstract: A vision-based experimental methodology was developed for monitoring the surface state evolution of specimens during bi-disc rolling contact tests, aimed at providing information for identifying the damage phenomena. The system is based on a high-speed camera and three laser pointers for illuminating the specimen surface. Images of the specimen surface are acquired and processed, allowing the definition of synthetic surface state indexes, as well as the 3D reconstruction of the damaged surface topology. The vision system was applied to alternated dry-wet rollingsliding contact tests on railway wheel steel specimens, highlighting its effectiveness in the damage evaluation.

Keywords: Damage assessment. | Image processing | Online monitoring | Rolling contact fatigue | Wear

Abstract: Given a to-be-watermarked 3D model, a transformed domain analysis is needed to guarantee a robust embedding without compromising the visual quality of the result. A multiresolution remeshing of the model allows to represent the 3D surface in a transformed domain suitable for embedding a robust and imperceptible watermark signal. Simplification of polygonal meshes is the basic step for a multiresolution remeshing of a 3D model; this step is needed to obtain the model approximation (coarse version) from which a refinement framework (i.e. 3D wavelet analysis, spectral analysis, …) able to represent the model at multiple resolution levels, can be performed. The simplification algorithm should satisfy some requirements to be used in a watermarking system: the repeatability of the simplification, and the robustness of it to noise or, more generally, to slight modifications of the full resolution mesh. The performance of a number of software packages for mesh simplification, including both commercial and academic offerings, are compared in this survey. We defined a benchmark for testing the different software in the watermarking scenario and reported a comprehensive analysis of the software performances based on the geometric distortions measurement of the simplified versions.

Keywords: 3D watermarking | Mesh comparison | Mesh simplification | Wavelets 3D

Abstract: This research aims to develop a system that examines and reacts to the changing behaviors and emotions of individuals in order to improve their shopping experience. The system is able to track emotions in real time at different touchpoints in a store and control a set of networked devices to configure the sensing space and all provided services responsive to the cus-tomers’ needs. This paper describes the general approach adopted to design the overall system and illustrates in detail the module prototyped to understand the users’ emotions through the analysis of facial expressions.

Keywords: Context-aware computing | Emotion recognition | Methods for CX | Shopping experience

Abstract: The visualization and analysis of mosaics and pavements are often compromised by their large sizes, which do not enable the observer to perceive their whole arrangement or to focus on details placed in farthest areas from its boundaries. Moreover, the usual precarious state of conservation of these artefacts, often with damaged or missing areas, makes it difficult to perceive their original aesthetic value. To overcome these limitations, we propose an application of augmented reality able to support the observer in two ways: first, the application completes the missing surface of the mosaic or pavement by integrating the existent surface with a virtual reconstruction; second, it enables the analysis of the geometric pattern of the mosaic/pavement by overlaying virtual lines and geometric figures in order to explicit its geometric arrangements. The result is achieved via a custom Android application able to recognize and track the mosaic figure pattern and extra marker board, obtaining in that way a coordinate system used to render in real-time the reconstruction of the mosaic. Such rendering is overlaid to the video stream of the real scene. The application runs on a standard smartphone embedded in a Google Cardboard-compatible viewer and therefore is extremely affordable. As a case study, in order to reconstruct its aspects and to analyse its geometric pattern, we chose the roman mosaic re-found in Savignano sul Panaro (near Modena, Italy) in 2011, after 115 years from its first discovery, which is preserved less than half of its original 4.5 x 6.9 m surface.

Keywords: Augmented Reality | Cultural heritage | Geometric pattern | Photogrammetry | Real-time visualization | Roman mosaic

Abstract: This paper proposes the integration of photogrammetric reconstruction, 3D modelling and augmented reality application in order to achieve the complete visualization of a stone sculpture even if highly damaged or fragmentary. The first part of the research aims to the reconstruction of the original aspect of an incomplete sculpture, by using photogrammetry techniques based on standard resolution photos and free software in order to obtain a first model; then, we integrate this model with other 3D digital data (from other sculptures of the same period) or with 3D modelling based on historical sources and views from historians, aiming to achieve the original aspect of the sculpture. The second part of the research consists of the embedding of the obtained model in a custom application able to render in real-time the 3D reconstruction of the lion. Then, the rendering is overlaid to the video stream of the real scene and, as a result, a complete 3D digital model of the sculpture is achieved and could be visualized through a VR viewer. As a case study, we focus on a Roman stone sculpture of a male lion conserved in the Museo Estense of Modena (Italy), which lacks of its head and its four legs. The original aspect of the lion may be achieved by integrating the damaged sculpture with other photogrammetric reconstructions of lions sculptures of the same period and with 3D model based on historical sources. Finally, the lion is visualized through an augmented reality application which digitally overlays the reconstructed models on the original one.

Keywords: Augmented Reality | Cultural heritage | Photogrammetry | Real-time visualization | Virtual modeling

Abstract: Meniscectomy significantly change the kinematics of the knee joint by reducing the contact area between femoral condyles and the tibial plateau, but the shift in the contact area has been poorly described. The aim of our investigation was to measure the shift of the tibiofemoral contact area occurring after meniscectomy. We used laser scans combined to surface texturing for measuring the 3D position and area of the femoral and tibial surfaces involved in the joint. In particular, natural condyles (porcine model) were analysed and the reverse engineering approach was used for the interpretation of the results from compression tests and local force measurements in conjunction with staining techniques. The results suggested that laser scans combined to surface texturing may be considered as a powerful tool to investigate the stained contours of the contact area. Beside the largely documented reduction of contact area and local pressure increase, a shift of the centroid of the contact area toward the intercondylar notch was measured after meniscectomy. As a consequence of the contact area shift and pressure increase, cartilage degeneration close to the intercondylar notch may occur.

Keywords: Biomechanics | Centroid | Image analysis | Laser scanning | Surface texturing | Tibiofemoral contact area

Abstract: In the Industry 4.0 and digital revolution era, the world of manufacturing industry is experiencing an innovative reconfiguration of design tools and methodologies, with a different approach to the production processes organization. The design philosophy is changing, integrating to engineering contribution interpretative aspects (design thinking), executive practices (design doing) and cognitive aspects (design cultures). The design becomes human-centered. The new Virtual Reality technologies allow to validate performances of designed products and production processes by means of virtual prototypes in a virtual simulated environment. This approach generates several benefits to the companies, in terms of costs and time, and allows optimizing the assembly line design and related workplaces, by improving workers' benefits too. This paper proposes an innovative method to validate the design of workplaces on automotive assembly lines in a virtual environment, based on ergonomic approach, according to ERGO - Uas system, applied by FCA (Fiat Chrysler Automobiles) groups, that integrates UAS method for measurement and EAWS method for biomechanical effort evaluation. Creating 3D virtual scenarios allows to carry on assembly tasks by virtual manikins in order to be evaluated from different points of view. In particular, data coming from the simulation can be used to assess several ergonomic indexes, improving safety, quality and design. The analysis is supported by the use of a motion capture system, developed by the University of Campania and composed of wearable inertial sensors, that estimates the attitude of fundamental human segments, using sensor fusion algorithms based on Kalman filtering. In this way, it is possible to make a further design validation, assessing the EAWS index basing on posture angles trends evaluated. This method can represent an innovation for human-centered design of workplace in developing new products, reducing costs and improving job quality.

Keywords: design | ergonomics | manufacturing | motion capture | product feasibility | simulation | Virtual reality

Abstract: Objectives To investigate the influence of specific resin-composite, glass ceramic and glass ionomer cement (GIC) material combinations in a “multi-layer” technique to replace enamel and dentin in class II mesio-occlusal-distal (MOD) dental restorations using 3D-Finite Element Analysis (FEA). Methods Four 3D-FE models (A–D) of teeth, adhesively restored with different filling materials, were created and analyzed in comparison with a 3D model (E) of a sound lower molar. Models A, B & C had “multilayer” constructions, consisting of three layers: adhesive, dentin replacement and enamel replacement. Model A: had a low modulus (8 GPa) composite replacing dentin and a higher modulus (12 GPa) composite replacing enamel. Model B: had a GI cement replacing dentin and a higher modulus (12 GPa) composite replacing enamel. Model C: had a low modulus (8 GPa) composite replacing dentin and a very high modulus (70 GPa) inlay replacing enamel. Model D: had a lithium disilicate inlay replacing both dentin and enamel with a luting cement base-layer. Polymerization shrinkage effects were simulated and a load of 600 N was applied. All the materials were assumed to behave elastically throughout the entire deformation. Results Model A showed the highest stress distribution along all the adhesive interfaces of the shrinking resin-based materials with a critical condition and failure risk marginally and internally. Model D, by contrast, showed a more favorable performance than either of the multilayer groups (A–C). Stress and displacement plots showed an elastic response similar to that obtained for the sound tooth model. Model B and Model C performed according to their bilayer material properties. The use of a non-shrink dentin component simulating a GIC clearly affected the shrinkage stress at the basis of the Model B; while the bulk resin composite having a 12 GPa Young's modulus and linear polymerization shrinkage of 1% strongly influenced the biomechanical response in the bucco-lingual direction. Significance Direct resin-based composite materials applied in multilayer techniques to large class II cavities, with or without shrinking dentin layers, produced adverse FEA stress distributions and displacements. An indirect lithium disilicate inlay used to replace lost dentin and enamel in posterior restored teeth generated lower stress levels, within the limits of the elastic FEA model.

Keywords: CAD | Class II restorations | Finite element analysis | Image analysis | Materials properties

Abstract: Objective To assess the effect of a ferrule design with specific post material-shape combinations on the mechanical behavior of post-restored canine teeth. Methods Micro-CT scan images of an intact canine were used to create a 3-D tessellated CAD model, from which the shapes of dentin, pulp and enamel were obtained and geometric models of post-endodontically restored teeth were created. Two types of 15 mm post were evaluated: a quartz fiber post with conical–tapered shape, and a carbon (C) fiber post with conical–cylindrical shape. The abutment was created around the coronal portion of the posts and 0.1 mm cement was added between prepared crown and abutment. Cement was also added between the post and root canal and a 0.25 mm periodontal ligament was modeled around the root. Four models were analysed by Finite Element (FE) Analysis: with/without a ferrule for both types of post material and shape. A load of 50 N was applied at 45° to the longitudinal axis of the tooth, acting on the palatal surface of the crown. The maximum normal stress criterion was adopted as a measure of potential damage. Results Models without a ferrule showed greater stresses (16.3 MPa) than those for models with a ferrule (9.2 MPa). With a ferrule, stress was uniformly distributed along the abutment and the root, with no critical stress concentration. In all models, the highest stresses were in the palatal wall of the root. Models with the C-fiber post had higher stress than models with the quartz fiber posts. The most uniform stress distribution was with the combination of ferrule and quartz fiber post. Significance The FE analysis confirmed a beneficial ferrule effect with the combination of ferrule and quartz fiber post, with tapered shape, affording no critical stress concentrations within the restored system.

Keywords: CAD | Dental materials | Endodontic treatment | Finite element analysis | Image analysis | Materials properties

Abstract: The use of polymer composites has been increasing over the years and nowadays the requirements for designing high performance and lightweight fabrics and laminates for sail manufacturing have become more stringent than ever. The present paper offers an effective methodology that enhances the understanding of the influence of fibres orientation and arrangement of panels on sail performance. Constitutive characteristics of the ten commonly used sail cloths are experimentally measured and their influence on sail dynamic performance is compared using an aerodynamic approach. As expected also in industry 4.0 the method allows to control the production process and final product optimization.

Keywords: Aerodynamic coefficient | Apparent wind angle (AWA) | Apparent Wind Speed (AWS) | CFD analysis | Digital photogrammetry | RE | Turbulence model

Abstract: Sail manufacture has undergone significant development due to sailing races like the America’s Cup and the Volvo around the World Race. These competitions require advanced technologies to help increase sail performance. Hull design is fundamentally important but the sails (the only propulsion instrument) play a key role in dynamic of sailboats. Under aerodynamic loads, sail cloth deforms, the aerodynamic interaction is modified and the pressure on the sails is variously distributed resulting in performance inconsistencies. The interaction between fluid and structure necessitates a solution which combines aerodynamic and structural numerical simulations. Furthermore, in numerical simulations the aeroelastic sail characteristics must be known accurately. In this paper, the dynamic performance of a Spinnaker was studied. Digital photogrammetry was used to acquire the images, make the 3D reconstruction of the sail and validate the models in Computational Fluid Dynamics (CFD) analysis. Orthotropic constitutive characteristics of ten different sail cloths were measured by experimental test. The methodology allowed to compare dynamic performance in terms of forces, pressure and vibration for the different sail cloths and different fiber orientations.

Keywords: CFD analysis | Detached eddy simulations | Pressure distributions | Sail aerodynamics | Turbulence models

Abstract: The Italian fashion industry is nowadays subject to radical transformation; therefore, it needs to remain competitive and, at the same time, innovate itself, in order to strengthen its position in the global market. An important opportunity of innovation can be the introduction of ICT technologies in the garment design process, which today is based on traditional methods and tools. Moreover, this innovation could be particularly important for online sales, in order to reduce the customers’ doubts during purchasing. The research presented in this paper describes a framework for designing clothes as realistic 3D digital models and for allowing customers to evaluate the designed clothes by using realistic virtual mannequins of their bodies instead of the standard ones. A case study will be presented in the paper. The obtained results show that the framework can innovate the traditional garment design process and it could have a huge impact on fashion industry and customers behaviours.

Keywords: Body scanning | Cloth simulation | Design process | Motion capture | Virtual prototype

Abstract: Background/purpose: We investigate the use of skin texture features from the inner forearm as a means for personal identification. The forearm offers a number of potential advantages in that it is a fairly accessible area, and, compared with other zones such as fingertips, is less exposed to the elements and more shielded from wear. Methods: We extract and combine skin textural features from two imaging devices (optical and capacitive) with the aim of discriminating between different individuals. Skin texture images from 43 subjects were acquired from three different body parts (back of the hand, forearm and palm); testing used the two sensors either separately or in combination. Results: Skin texture features from the forearm proved effective for discriminating between different individuals with overall recognition accuracy approaching 96%. Conclusions: We found that skin texture features from the forearm are highly individual-specific and therefore suitable for personal identification. Interestingly, forearm skin texture features yielded significantly better accuracy compared to the skin of the back of the hand and of the palm of the same subjects.

Keywords: image processing | personal identification | skin texture | texture analysis

Abstract: Skin appearance is almost universally the object of gender-related expectations and stereotypes. This not with standing, remarkably little work has been done on establishing quantitatively whether skin texture can be used for gender discrimination. We present a detailed analysis of the skin texture of 43 subjects based on two complementary imaging modalities afforded by a visible-light dermoscope and the recently developed Epsilon sensor for capacitive imaging. We consider an array of established texture features in combination with two supervised classification techniques (1-NN and SVM) and a state-of-the-art unsupervised approach (t-SNE). A statistical analysis of the results suggests that skin microtexture carries very little information on gender.

Keywords: Gender recognition | Skin | SVM | Texture

Abstract: A simple and compact Depth-From-Defocus (DFD) setup, using telecentric illumination and liquid-lens based camera observation, was shown to perform well for 3D shape acquisition over extended measuring range. A further step to ameliorate the system performance is described in this paper. We focused on finding an algorithm to speed up the calibration step of the method, that automatically determines the minimum number of focal lengths to be used in the calibration and measurement procedure. As a result, the calibration is significantly shortened (up to 80% with respect to the original procedure), and the need to manually (and to some extent arbitrarily) select the focal length pairs is overcome. Measurement errors down to 0.73 mm over the measurement depth range of 130 mm, corresponding to 0.55% of the depth range are achieved, in total agreement with the original system.

Keywords: Calibration | Depth From Defocus | Image processing | Liquid lenses | Phase modulation | Shape measurement

Abstract: We present the in-field use of a recently developed on-line, real time, optical monitoring system for bi-disk rolling contact tests on railway-wheel- and rail- steel disks, based on laser illumination and a high-speed camera. Qualitative, as well as quantitative information can be obtained by the use of specific indexes derived from the images using blob analysis. Monitoring the tests provides information about the initial transients of turning-crest removal, on the steady state reached, and on the dynamics of the surface in between. Blob anisotropy is a key element to draw information of the mechanisms governing this intermediate state.

Abstract: A novel depth from defocus (DFD) measurement system is presented, where the extension of the measurement range is performed using an emergent technology based on liquid lenses. A suitable set of different focal lengths, obtained by properly changing the liquid lens supply voltage, provides multiple camera settings without duplicating the system elements or using moving parts. A simple and compact setup, with a single camera/illuminator coaxial assembly, is obtained. The measurement is based on an active DFD technique using modulation measurement profilometry for the estimation of the contrast at each image point as a function of the depth range. Two different measurement methods are proposed, both based on a combination of multiple contrast curves, each derived at a specific focal length. In the first method (intensity contrast method), the depth information is recovered directly from the contrast curves, whereas in the second (differential contrast method), the depth is measured using contrast curve pairs. We obtained a measurement σ0 of 0.55 mm over a depth range of 60 mm with the intensity contrast method (0.92% of the total range) and an σ0 of 0.76 mm over a depth range of 135 mm with the differential contrast method (0.56% of the total range). Thus, the intensity contrast method is within the state-of-the-art DFD systems, whereas the differential contrast method allows, σ0 being almost equal, a remarkable extension of the depth range.

Keywords: Calibration | image edge analysis | image processing | lenses | phase modulation | shape measurement

Abstract: Wear and Rolling Contact Fatigue (RCF) tests on wheel/rail specimens are important to develop wheels of new materials for improved lifetime and performance, able to operate in harsh environments and at high rolling speeds. We have studied the feasibility of a novel non-invasive all-optical system, based on a high-speed video camera and two laser illumination sources, which is able to continuously monitor the dynamics of the specimens used to test wheel and rail materials, in a laboratory test bench. Surface micro- and macrotopography are monitored using blob analysis and 3D laser triangulation respectively. Blob analysis yields to good discrimination among the specimens, in terms of wear induced surface damage; the 3D measurement, which is characterized by a resolution of 0.033 mm, is able to monitor RCF effects. The system is described with the aid of end-cycle specimens, as well as of intermediate specimens, prior to its installation in the test bench for rolling contact tests.

Abstract: This work describes a simple, fast, and robust method for identifying, checking and managing the overlapping image keypoints for 3D reconstruction of large objects with numerous geometric singularities and multiple features at different lighting levels. In particular a precision 3D reconstruction of an extensive architecture captured by aerial digital photogrammetry using Unmanned Aerial Vehicles (UAV) is developed. The method was experimentally applied to survey and reconstruct the 'Saraceni' Bridge' at Adrano (Sicily), a valuable example of Roman architecture in brick of historical/cultural interest. The variety of features and different lighting levels required robust self-correlation techniques which would recognise features sometimes even smaller than a pixel in the digital images so as to automatically identify the keypoints necessary for image overlapping and 3D reconstruction. Feature Based Matching (FBM) was used for the low lighting areas like the intrados and the inner arch surfaces, and Area Based Matching (ABM) was used in conjunction to capture the sides and upper surfaces of the bridge. Applying SIFT (Scale Invariant Feature Transform) algorithm during capture helped find distinct features invariant to position, scale and rotation as well as robust for the affinity transformations (changes in scale, rotation, size and position) and lighting variations which are particularly effective in image overlapping. Errors were compared with surveys by total station theodolites, GPS and laser systems. The method can facilitate reconstruction of the most difficult to access parts like the arch intrados and the bridge cavities with high correlation indices.

Keywords: Architectural reconstruction | Area Based Matching | Feature Based Matching | Photogrammetry | SIFT algorithm

Abstract: Shape from shading (SFS) denotes the problem of reconstructing a 3D surface, starting from a single shaded image which represents the surface itself. Minimization techniques are commonly used for solving the SFS problem, where the objective function is a weighted combination of the brightness error, plus one or more terms aiming to obtain a valid solution. We present a regularized quadratic penalty method where quadratic penalization is used to adaptively adjust the smoothing weights, and regularization improves the robustness and reliability of the procedure. A nonmonotone Barzilai–Borwein method is employed to efficiently solve the arising subproblems. Numerical results are provided showing the reliability of the proposed approach.

Keywords: Barzilai–Borwein method | quadratic penalty methods | quadratic regularization | Shape from shading

Abstract: The paper deals with an experimental assessment of the Leap Motion Controller®. This device is able to track the user’s hands in a real environment. Due to low-invasiveness and easiness of use, it is promising for the integration in virtual or augmented reality, research and entertainment scenarios. The assessment is performed in a real context using volunteers that were asked to point with the fingertips to a set of predefined locations in space. A specific test rig has been designed and built. It is comprised of a transparent plate supported by adjustable pillars and mounted over the Leap. The data are processed to assess the errors in tracking the five fingertips of the right hand. Results show that the accuracy and precision of the Leap is suitable for robust tracking of the user’s hand. The results also unveil that there are preferable zones in which the tracking performance is better.

Keywords: Leap controller | Motion capture | Natural interface | Tracking | User interaction

Abstract: The paper explores the possibility of using low-cost motion capture technologies to automatically evaluate patient’s condition concerning his/her walking condition. Two different technologies, optical markerless and inertial, are used to track the gait to be adopted in a doctor’s office or at patient’s home. The data acquired are elaborated using commercial and in-house developed tools with the aim of creating, in a near future, a simple environment for medical staff and people non highly skilled in IC technology. The paper shows the feasibility of an automatic detection of a set of gait abnormalities affecting people having a lower limb prosthesis. This constitutes a robust support for orthopedic technicians work and foresees the use of such technology for larger surveys and early detection of gait deviations.

Keywords: Gait Analysis | Inertial sensors | Motion Capture | RGB-D sensors

Abstract: One of the most important parameters to be controlled during the production of textile yarns obtained by mixing pre-colored fibers, is the color correspondence between the manufactured yarn and a given reference, usually provided by a designer or a customer. Obtaining yarns from raw pre-colored fibers is a complex manufacturing process entailing a number of steps such as laboratory sampling, color recipe corrections, blowing, carding and spinning. Carding process is the one devoted to transform a “fuzzy mass” of tufted fibers into a regular mass of untwisted fibers, named “tow”. During this process, unfortunately, the correspondence between the color of the tow and the target one cannot be assured, thus leading to yarns whose color differs from the one used for reference. To solve this issue, the main aim of this work is to provide a system able to perform a spectral camera-based real-time measurement of a carded tow, to assess its color correspondence with a reference carded fabric and, at the same time, to monitor the overall quality of the tow during the carding process. Tested against a number of differently colored carded fabrics, the proposed system proved its effectiveness in reliably assessing color correspondence in real-time.

Keywords: Carding process | Color assessment | Spectral camera sensor | Spectrophotometry

Abstract: The stylistic design of new industrial products often starts from shaded handmade sketches which, usually, need to be converted into 3D digital models by using CAD software packages for the subsequent design phases. This conversion often represents the bottleneck of the whole development process. Shape from Shading (SFS), which attempts to recover the 3D geometry of an object starting from a single shaded representation, is potentially capable of speeding-up the 3D conversion. However, existing approaches prove to be extremely unstable and error prone mainly due to the under-determination of the SFS problem. In order to increase the performance of shading based reconstruction authors propose a step-by-step variational-based approach. In particular, the problem is solved into multiple steps, each one providing the initialization for the following, so that the solution gradually converges towards the final surface. Tested against a set of case studies, the method proved its effectiveness.

Keywords: 3D design | Computer aided design | Numerical optimization | Shape from shading | Stylistic content | Variational approach

Abstract: Minimization techniques are widely used for retrieving a 3D surface starting from a single shaded image i.e., for solving the shape from shading problem. Such techniques are based on the assumption that expected surface to be retrieved coincides with the one that minimize a properly developed functional, consisting of several contributions. Among the possible contributes defining the functional, the so called "smoothness constraint" is always used since it guides the convergence of the minimization process towards a more accurate solution. Unfortunately, in areas where actually brightness changes rapidly, it also introduces an undesired over-smoothing effect. The present work proposes two simple yet effective strategies for avoiding the typical over-smoothing effect, with regards to the image regions in which this effect is particularly undesired (e.g., areas where surface details are to be preserved in the reconstruction). Tested against a set of case studies the strategies prove to outperform traditional SFS-based methods.

Keywords: 3D model | Minimization | Shape from shading | Smoothing | Smoothness constraint | Variational approach

Abstract: A family of 26 non-parametric texture descriptors based on Histograms of Equivalent Patterns (HEP) has been tested, many of them for the first time in remote sensing applications, to improve urban classification through object-based image analysis of GeoEye-1 imagery. These HEP descriptors have been compared to the widely known texture measures derived from the gray-level co-occurrence matrix (GLCM). All the five finally selected HEP descriptors (Local Binary Patterns, Improved Local Binary Patterns, Binary Gradient Contours and two different combinations of Completed Local Binary Patterns) performed faster in terms of execution time and yielded significantly better accuracy figures than GLCM features. Moreover, the HEP texture descriptors provided additional information to the basic spectral features from the GeoEye-1’s bands (R, G, B, NIR, PAN) significantly improving overall accuracy values by around 3%. Conversely, and in statistic terms, strategies involving GLCM texture derivatives did not improve the classification accuracy achieved from only the spectral information. Lastly, both approaches (HEP and GLCM) showed similar behavior with regard to the training set size applied.

Keywords: GeoEye-1 | Histograms of equivalent patterns | OBIA | Texture

Abstract: The size distribution of aggregates has direct and important effects on fundamental properties of construction materials such as workability, strength and durability. The size distribution of aggregates from construction and demolition waste (C&D) is one of the parameters which determine the degree of recyclability and therefore the quality of such materials. Unfortunately, standard methods like sieving or laser diffraction can be either very time consuming (sieving) or possible only in laboratory conditions (laser diffraction). As an alternative we propose and evaluate the use of image analysis to estimate the size distribution of aggregates from C&D in a fast yet accurate manner. The effectiveness of the procedure was tested on aggregates generated by an existing C&D mechanical treatment plant. Experimental comparison with manual sieving showed agreement in the range 81-85%. The proposed technique demonstrated potential for being used on on-line systems within mechanical treatment plants of C&D.

Keywords: Construction and demolition waste | Image analysis | Particle size distribution | Texture

Abstract: This paper presents the advancements of an automatic segmentation procedure based on the concept of Hierarchical Space Partitioning. It is aimed at tolerance inspection of electromechanical parts produced by injection moulding and acquired by laser scanning. After a general overview of the procedure, its application for recognising cylindrical surfaces is presented and discussed through a specific industrial test case.

Keywords: Computer aided tolerancing & inspection | Hierarchical space partitioning | Injection moulding | Reverse engineering

Abstract: Rolling contact wear/fatigue tests on wheel/rail specimens are important to produce wheels and rails of new materials for improved lifetime and performance, which are able to operate in harsh environments and at high rolling speeds. This paper presents a novel non-invasive, all-optical system, based on a high-speed video camera and multiple laser illumination sources, which is able to continuously monitor the dynamics of the specimens used to test wheel and rail materials, in a laboratory test bench. 3D macro-topography and angular position of the specimen are simultaneously performed, together with the acquisition of surface micro-topography, at speeds up to 500 rpm, making use of a fast camera and image processing algorithms. Synthetic indexes for surface micro-topography classification are defined, the 3D macro-topography is measured with a standard uncertainty down to 0.019 mm, and the angular position is measured on a purposely developed analog encoder with a standard uncertainty of 2.9°. The very small camera exposure time enables to obtain blur-free images with excellent definition. The system will be described with the aid of end-cycle specimens, as well as of in-test specimens.

Abstract: A fast and reliable optical setup is here presented for in-focus imaging of objects in the macro range. The setup uses a camera equipped with an objective embedding a liquid lens, whose focal length is voltage-controlled. The defocus condition of the image is controlled by means of two indexes, both suitable for coarse and for fine adjustments. A purposely designed algorithm makes use of the two indexes, switching from one to the other to position the image in focus by adequately controlling the liquid lens focal length. The setup has been calibrated by means of target planes of known contrasts, and applied to process biomedical images such as fingerprints.

Abstract: Innovation of fashion-related products implies the continuous search for new and appealing shapes and materials in a short period of time due to the seasonality of the market. The design and manufacturing of such products have to deal with a dimensional variability as a consequence of the new shapes. An additional difficulty concerns properly forecasting the technological behaviour of the new materials in relation to the manufacturing process phases. The control of dimensional variations requires time and resource intensive activities. Human's manual and visual inspection solutions are more common than automatic ones for performing such control, where skilled operators are typically the only ones capable of immediately facing non-standard situations. The full control of such variations is even more subtle and mandatory in the field of spectacles, which are fashion-related products and also medical devices. This paper describes an inspection system developed to monitor the dimensional variations of a spectacles frame during the manufacturing process. We discuss the methodological approach followed to develop the system, and the experimental campaign carried out to test its effectiveness. The system intends to be an alternative to current inspection practices used in the field, and also to provide a methodological approach to enable engineers to systematically study the correlations existing among the frame main functional and dimensional parameters, the material behaviour and the technological variables of the manufacturing process. Hence, the system can be considered a method to systematically acquire and formalise new knowledge. The inspection system consists of a workbench equipped with four high-quality commercial webcams that are used to acquire orthogonal-view images of the front of the frame. A software module controls the system and allows the automatic processing of the images acquired, in order to extract the dimensional data of the frame which are relevant for the analysis. A case study is discussed to demonstrate the system performances.

Keywords: Eyewear industry | Image processing | Inspection systems | Knowledge-based engineering | Product variability

Abstract: The paper describes a system to supply meaningful insights to designers during the concept generation of new car interiors. The aim of the system is to capture the movements of car passenger's and making these acquisitions directly available as a generative input. The system has been developed by integrating the Abstract Prototyping technique with Motion Capture technology. In addition, a systematic procedure allows the treatment of the collected data to obtain a graphical representation, which can be easily used with standard NURBS-based modeling software. The effectiveness of the system has been evaluated through a testing session conducted with subjects. The outcomes of the testing sessions have highlighted benefits and limitations of the implemented system.

Keywords: Abstract prototyping | human factors | motion capture

Abstract: Color matching of fabric blends is a key issue for the textile industry, mainly due to the rising need to create high-quality products for the fashion market. The process of mixing together differently colored fibers to match a desired color is usually performed by using some historical recipes, skillfully managed by company colorists. More often than desired, the first attempt in creating a blend is not satisfactory, thus requiring the experts to spend efforts in changing the recipe with a trial-and-error process. To confront this issue, a number of computer-based methods have been proposed in the last decades, roughly classified into theoretical and artificial neural network (ANN)-based approaches. Inspired by the above literature, the present paper provides a method for accurate estimation of spectrophotometric response of a textile blend composed of differently colored fibers made of different materials. In particular, the performance of the Kubelka-Munk (K-M) theory is enhanced by introducing an artificial intelligence approach to determine a more consistent value of the nonlinear function relationship between the blend and its components. Therefore, a hybrid K-M+ANN-based method capable of modeling the color mixing mechanism is devised to predict the reflectance values of a blend.

Keywords: computer-based color assessment | fabric blend | Kubelka-Munk theory | neural networks | spectrophotometer

Abstract: Digital documentation and high-quality 3D representation are always more requested in many disciplines and areas due to the large amount of technologies and data available for fast, detailed and quick documentation. This work aims to investigate the area of medium and small sized artefacts and presents a fast and low cost acquisition system that guarantees the creation of 3D models with an high level of detail, making the digitalization of cultural heritage a simply and fast procedure. The 3D models of the artefacts are created with the photogrammetric technique Structure From Motion that makes it possible to obtain, in addition to three-dimensional models, high-definition images for a deepened study and understanding of the artefacts. For the survey of small objects (only few centimetres) it is used a macro lens and the focus stacking, a photographic technique that consists in capturing a stack of images at different focus planes for each camera pose so that is possible to obtain a final image with a higher depth of field. The acquisition with focus stacking technique has been finally validated with an acquisition with laser triangulation scanner Minolta that demonstrates the validity compatible with the allowable error in relation to the expected precision.

Keywords: Cultural heritage | Focus stacking | Photogrammetry | Small artefacts | Structure from motion

Abstract: The integration of underwater 3D data captured by acoustic and optical systems is a promising technique in various applications such as mapping or vehicle navigation. It allows for compensating the drawbacks of the low resolution of acoustic sensors and the limitations of optical sensors in bad visibility conditions. Aligning these data is a challenging problem, as it is hard to make a point-to-point correspondence. This paper presents a multi-sensor registration for the automatic integration of 3D data acquired from a stereovision system and a 3D acoustic camera in close-range acquisition. An appropriate rig has been used in the laboratory tests to determine the relative position between the two sensor frames. The experimental results show that our alignment approach, based on the acquisition of a rig in several poses, can be adopted to estimate the rigid transformation between the two heterogeneous sensors. A first estimation of the unknown geometric transformation is obtained by a registration of the two 3D point clouds, but it ends up to be strongly affected by noise and data dispersion. A robust and optimal estimation is obtained by a statistical processing of the transformations computed for each pose. The effectiveness of the method has been demonstrated in this first experimentation of the proposed 3D opto-acoustic camera.

Keywords: Optical and acoustic integration | Opto-acoustic vision | ROV navigation | Underwater 3D imaging

Abstract: The diffusion of depth sensors to sense people and objects constitutes an outstanding opportunity in those fields in which the benefits of optical marker-less solutions for scanning or tracking are requested. This paper shows how two different applications based on MS Kinect device can be accomplished in the domain of lower limb prosthesis design and test. The first one refers to the use of a depth camera as a three-dimensional scanner to acquire the geometry of residual limbs or of custom-fit components. The second application is related to the motion capture of patients' gait with the prosthesis. In both cases, the technology resulted to be better than many traditional ones mainly for its limited invasivity, interesting performance, portability and low cost.

Keywords: 3D scanner | Digital human modelling | Lower limb prosthesis | Motion capture | RGB-D cameras

Abstract: The diffusion of depth sensors to sense people and objects constitutes an outstanding opportunity in those fields in which the benefits of optical marker-less solutions for scanning or tracking are requested. This paper shows how two different applications based on MS Kinect device can be accomplished in the domain of lower limb prosthesis design and test. The first one refers to the use of a depth camera as a three-dimensional scanner to acquire the geometry of residual limbs or of custom-fit components. The second application is related to the motion capture of patients' gait with the prosthesis. In both cases, the technology resulted to be better than many traditional ones mainly for its limited invasivity, interesting performance, portability and low cost.

Keywords: 3D scanner | Digital human modelling | Lower limb prosthesis | Motion capture | RGB-D cameras

Abstract: This paper presents a new methodology for computing grey-scale granulometries and estimating the mean size of fine and coarse aggregates. The proposed approach employs area morphology and combines the information derived from both openings and closings to determine the size distribution. The method, which we refer to as bipolar area morphology (BAM), is general and can operate on particles of different size and shape. The effectiveness of the procedure was validated on a set of 13 classes of aggregates of size ranging from 0.125 to 16 mm and made a comparison with standard, fixed-shape granulometry. In the experiments our model consistently outperformed the standard approach and predicted the correct size class with overall accuracy over 92 %. Tests on three classes from real samples also confirmed the potential of the method for application in real scenarios.

Keywords: Aggregates | Area morphology | Granulometry | Image analysis

Abstract: The injection of urea-water sprays within selective catalytic reduction systems is currently the leading technique for reducing the emission of nitrogen oxides from Diesel engines. For the process to work properly, it is crucial to guarantee the adequate size, velocity and distribution of the spray droplets upstream of the catalyst. It is therefore extremely important to understand the process of spray formation and evolution as well as possible. In this paper we describe a new methodology for inspecting the behaviour of urea-water sprays in realistic conditions. Our approach is based on a hot-air flow tunnel enabling optical inspection of the spray through phase-Doppler anemometry and back-light imaging. The procedure was employed to investigate the global and local characteristics of urea-water sprays under different flow conditions. The results proved the significant influence exerted by the flow conditions on the spray behaviour, and confirmed that the proposed system can provide considerable insight about the evolution of urea-water sprays. Cross-comparison of the droplet size estimated through phase-Doppler anemometry and back-light imaging showed substantial agreement between the two methods. This result suggests that back-light imaging is a viable alternative in those cases where complex exhaust geometry impedes the use of phase-Doppler anemometry.

Keywords: Image processing | Nitrogen oxides | Phase-Doppler anemometry | Selective catalytic reduction | Urea-water sprays

Abstract: In this work we propose the use of image features based on visual perception for discriminating epithelium and stroma in histological images. In particular, we assess the capability of the following five visual features to correctly discriminate epithelium from stroma in digitised tissue micro-arrays of colorectal cancer: coarseness, contrast, directionality, line-likeliness and roughness. The use of features directly related to human perception makes it possible to evaluate the tissue's appearance on the basis of a set of meaningful parameters; moreover, the number of features used to discriminate epithelium from stroma is very small. In the experiments we used histologically-verified, well-defined images of epithelium and stroma to train three classifiers based on Support Vector Machines (SVM), Nearest Neighbour rule (1-NN) and Naïve Bayes rule (NB). We optimised SVM's parameters on a validation set, and estimated the accuracy of the three classifiers on a independent test set. The experiments demonstrate that the proposed features can correctly discriminate epithelium from stroma with state-of-the-art accuracy.

Keywords: Colorectal cancer | Epithelium | Image analysis | Perceptual features | Stroma

Abstract: Human movements express non-verbal communication: The way humans move, live and act within a space influences and reflects the experience with a product. The study of postures and gestures can bring meaningful information to the design process. This paper explores the possibility to adopt Motion Capture technologies to inform the design process and stimulate concept generation with an Experience Design perspective. Motion data could enable designers to tackle Experience-driven design process and come up with innovative designs. However, due to their computational nature, these data are largely inaccessible for designers. This study presents a method to process the raw data coming from the Motion Capture system, with the final goal of reaching a comprehensible visualization of human movements in a modelling environment. The method was implemented and applied to a case study focused on User Experience within the car space. Furthermore, the paper presents a discussion about the conceptualization of human movement, as a way to inform and facilitate Experience-driven design process, and includes some propositions of applicable design domains.

Keywords: Body tracking | Conceptual design | Data visualization | Motion capture | User experience

Abstract: Beyond ergonomic measurements, the study of human movements can help designers in exploring the rich, non-verbal communication of users’ perception of products. This paper explores the ability of human gestures to express subjective experiences and therefore, to inform the design process at its early stages. We will investigate the traditional techniques used in the Experience Design domain to observe human gestures, and propose a method to couple Experience-driven design approach with Motion Capture technique. This will allow integrating qualitative user observations with quantitative and measurable data. However, the richness of information that Motion Capture can retrieve is usually inaccessible for designers. This paper presents a method to visualize human motion data so that designers can make sense of them, and use them as the starting point for concept generation.

Keywords: Body Tracking | Concept design | Data visualization | Motion Capture | User experience

Abstract: The maturity reached in the development of Unmanned Air Vehicles (UAVs) systems is making them more and more attractive for a vast number of civil missions. Clearly, the introduction of UAVs in the civil airspace requiring practical and effective regulation is one of the most critical issues being currently discussed. As several civil air authorities report in their regulations "Sense and Avoid" or "Detect and Avoid" capabilities are critical to the successful integration of UAV into the civil airspace. One possible approach to achieve this capability, specifically for operations beyond the Line-of-Sight, would be to equip air vehicles with a vision-based system using cameras to monitor the surrounding air space and to classify other air vehicles flying in close proximity. This paper presents an image-based application for the supervised classification of air vehicles. First, several vehicle images, taken from different points of view, are transformed using a descriptor of salient features as to build the five-class database used to train the classification algorithm. Then, the latter compares the descriptor of a vehicle image taken from a random point of view to records in the database. With a positive match, the vehicle will be assigned to one of the following classes: a) civil transport aircrafts, b) military aircrafts, c) general aviation aircrafts, d) helicopters, and e) airships/hot air balloons. The paper provides a possible layout for the algorithm implementation and presents the outcome of several tests performed to evaluate its efficiency and possible exploitation. Indications useful to further studies are presented to help future researches.

Abstract: Pilling is an undesired defect of textile fabrics, consisting of a surface characterized by a number of roughly spherical masses made of entangled fibers. Mainly caused by the abrasion of fabric surface occurring during washing and wearing of fabrics, this defect needs to be accurately controlled and measured by companies working in the textile industry. Pilling measurement is traditionally performed using manual procedures involving visual control of fabric surface by human experts. Since the early nineties, great efforts in developing automatic and non-intrusive methods for pilling measurement have been made all around the world with the final aim of overcoming traditional, visual-based and subjective procedures. Machine Vision proved to be among the best options to perform such defect assessment since it provided increasingly performing measurement equipment and tools, serving the purpose of automatic control. In particular, a relevant number of interesting works have been proposed so far, sharing the idea of helping (or even replacing) traditional measurement methods using image processing-based ones. The present work provides a rational and chronological review of the most relevant methods for pilling measurement proposed so far. This work serves the purposes of 1) understanding whether today’s automatic machine vision-based pilling measurement techniques are ready for supplanting traditional pilling measurement and 2) providing textile technology researchers with a bird’s eye view of the main methods studied to confront with this problem.

Keywords: Artificial neural networks | Fabrics | Image processing | Machine vision | Pilling assessment | Review

Abstract: Textile companies usually manufacture fabrics using a mix of pre-colored fibers according to a traditional recipe based on their own experience. Unfortunately, mainly due to the fibers dyeing process, the colorimetric distance between the obtained fabric and the desired one results unsatisfactory with respect to a colorimetric threshold established by the technicians. In such cases, colorists are required to slightly change the original recipe in order to reduce the colorimetric distance. This trial and error process is time-consuming and requires the work of highly skilled operators. Computer-based color recipe assessment methods have been proposed so far in scientific literature to address this issue. Unlikely, many methods are still far to be reliably predictive when the fabric is composed by a high number of components. Accordingly, the present work proposes two alternative methods based on Kubelka-Munk and subtractive mixing able to perform a reliable prediction of the spectrophotometric response of a fabric obtained by means of any variation of a recipe. The assessment performed on a prototypal implementation of the two methods demonstrates that they are suitable for reliable prediction of fabric blends spectral response.

Keywords: Computer-based color assessment | Fabric blend | Kubelka-Munk theory | Spectro-photometer

Abstract: Remotely Operated underwater Vehicles (ROVs) play an important role in a number of operations conducted in shallow and deep water (e.g.: exploration, survey, intervention, etc.), in several application fields like marine science, offshore construction, and underwater archeology. ROVs are usually equipped with different imaging devices, both optical and acoustic. Optical sensors are able to generate better images in close range and clear water conditions, while acoustic systems are usually employed in long range acquisitions and do not suffer from the presence of turbidity, a well-known cause of coarser resolution and harder data extraction. In this work we describe the preliminary steps in the development of an opto-acoustic camera able to provide an on-line 3D reconstruction of the acquired scene. Taking full advantage of the benefits arising from the opto-acoustic data fusion techniques, the system was conceived as a support tool for ROV operators during the navigation in turbid waters, or in operations conducted by means of mechanical manipulators. The paper presents an overview of the device, an ad-hoc methodology for the extrinsic calibration of the system and a custom software developed to control the opto-acoustic camera and supply the operator with visual information.

Keywords: 3D opto-acoustic camera | Optical and acoustic data fusion | ROV guidance | Stereovision system | System calibration

Abstract: Recovering correct or at least realistic colors of underwater scenes is a very challenging issue for imaging techniques, since illumination conditions in a refractive and turbid medium as the sea are seriously altered. The need to correct colors of underwater images or videos is an important task required in all image-based applications like 3D imaging, navigation, documentation, etc. Many imaging enhancement methods have been proposed in literature for these purposes. The advantage of these methods is that they do not require the knowledge of the medium physical parameters while some image adjustments can be performed manually (as histogram stretching) or automatically by algorithms based on some criteria as suggested from computational color constancy methods. One of the most popular criterion is based on gray-world hypothesis, which assumes that the average of the captured image should be gray. An interesting application of this assumption is performed in the Ruderman opponent color space lαβ, used in a previous work for hue correction of images captured under colored light sources, which allows to separate the luminance component of the scene from its chromatic components. In this work, we present the first proposal for color correction of underwater images by using lαβ color space. In particular, the chromatic components are changed moving their distributions around the white point (white balancing) and histogram cutoff and stretching of the luminance component is performed to improve image contrast. The experimental results demonstrate the effectiveness of this method under gray-world assumption and supposing uniform illumination of the scene. Moreover, due to its low computational cost it is suitable for real-time implementation.

Keywords: Color correction | Computational color constancy | Ruderman space | Underwater imaging

Abstract: First target of this paper is to describe the design the behaviour of the final prototype before its manufacturing of an automotive semi-active differential based on the use of a and to predict its good performances and possible Magnetorheological Fluid (MRF). The MRF allows to control weaknesses. So the costs and the time to market of the new the locking torque and, consequently, to improve the vehicle handling. Second target is to propose a method grounded on a Close-Range Photogrammetry approach for the CAD modeling phase of the device ideated, alternative to the use of the typical Reverse Engineering (RE) techniques. In fact, although a Reverse Engineering process allows the complete 3D reconstruction of the external surfaces and features of a real object, it could often take a lot of time and, in some cases, could be affected by some approximations or errors. Furthermore, a model “reconstructed” could not be the best solution for multiphysics analyses, where the parametric geometry is needed for the modifications of all its features and dimensions for the optimization process in a very short time. For these reasons, in the case studied, the complete CAD prototype, created step by step, is needed and the photogrammetry can represent an interesting solution to enhance the virtual prototyping phase without repercussions on the quality of the results. Starting from the acquisition of particular “key points”, with an acceptable tolerance, the definition of the references (datum axes, curves, planes, centres of holes) needed for the CAD modeling, according to the Top-Down procedure, was possible. Once obtained the preliminary prototype, the final CAD model was created optimizing its dimensions and choosing the adequate materials. To evaluate the goodness of the procedure adopted, the MRF LSD geometry was reconstructed also by means of the Reverse Engineering techniques applied to the physical prototype of the new device ad hoc created. In particular, laser system acquisition and RE dedicated software were used. In this way the comparison between the photogrammetric and Reverse Engineering procedures (in terms of time spent and quality of the results) was allowed and so conducted. Lastly, the results of the FEM analyses carried out to validate the design process and the methodology ideated and adopted were showed.

Keywords: 3D CAD parametric modeling | Automotive differential | Direct modeling | FEM analysis | Magnetorheological fluid | Photogrammetry | Reverse engineering

Abstract: Seagrass meadows are complex ecosystems representing an important source of biodiversity for coastal marine systems, but are subjected to numerous threats from natural and human-based influences. Due to their susceptibility to changing environmental conditions, seagrasses are habitually used in monitoring programmes as biological indicators to assess the ecological status of coastal environments. In this paper we used a non-destructive photo mosaicing technology to quantify seagrass distribution and abundance, and explore benefits of micro-cartographic analysis. Furthermore, the use of photogrammetric tools enhanced the method, which proved to be efficient due to its use of low-cost instruments and its simplicity of implementation. This paper describes the steps required to use this method in meadows of Posidonia oceanica, including: i) camera calibration procedures, ii) programming of video survey, iii) criteria to perform sampling activities, iv) data processing and micro-georeferenced maps restitution, and v) possible study applications.

Keywords: Mapping | Photo mosaicing | Photogrammetry | Posidonia oceanica | Seagrass | Underwater photography

Abstract: Motion capture of the human body has being performed for decades with a growing number of technologies, aims and application fields; but only recent optical markerless technologies based on silhouette recognition and depth sensors which have been developed for videogames control interface have brought motion capture to a broad diffusion. Actually, nowadays there are low cost hardware and software suitable for a wide range of applications that may vary from entertainment domain (e.g., videogames, virtual characters in movies) to the biomechanical and biomedical domain (e.g., gait analysis or orthopedic rehabilitation) and to a huge number of industrial sectors. In this quick evolving scenario it is hard to tell which technology is the most suitable for any desired goal. The aim of the paper is to answer to this issue by presenting a benchmark analysis that compares RGB and RGB-D technologies used to track performing people in a variety of conditions. In order to contrast the solutions, several different tasks have been selected, simultaneously captured and post-processed exactly in the same way. The test campaign has been designed to evaluate pros and cons according to the most important feature of a motion capture technology, such as volume of acquisition, accuracy of joint position and tracking of fast movements. Actors were asked to perform a number of tasks, among which free movements of arms, legs and full body, gait, and tasks performed interacting with a machine. The number of sensors around the scene and their disposition have been considered as well. We used Sony PS Eye cameras and Microsoft Kinect sensors as hardware solutions and iPisoft for data elaboration. The gathered results are organized, compared and discussed stressing performances and limitations of any combination and, at last, we proposed the best candidate technology for some key applications.

Keywords: Benchmark | Depth cameras | Digital Human Models | Motion capture | RGB | RGB-D

Abstract: Pilling is a complex property of textile fabrics, representing, for the final user, a non-desired feature to be controlled and measured by companies working in the textile industry. Traditionally, pilling is assessed by visually comparing fabrics with reference to a set of standard images, thus often resulting in inconsistent quality control. A number of methods using machine vision have been proposed all over the world, with almost all sharing the idea that pilling can be assessed by determining the number of pills or the area occupied by the pills on the fabric surface. In the present work a different approach is proposed: instead of determining the number of pills, a machine vision-based procedure is devised with the aim of extracting a number of parameters characterizing the fabric. These are then used to train an artificial neural network to automatically grade the fabrics in terms of pilling. Tested against a set of differently pilled fabrics, the method shows its effectiveness.

Keywords: Computational vision | Image processing | Machine vision system | Neural networks | Pilling | Textile industry

Abstract: Commonly used to produce the visual effect of full 3D scene on reduced depth supports, bas relief can be successfully employed to help blind people to access inherently bi-dimensional works of art. Despite a number of methods have been proposed dealing with the issue of recovering 3D or 2.5D surfaces from single images, only a few of them explicitly address the recovery problem from paintings and, more specifically, the needs of visually impaired and blind people. The main aim of the present paper is to provide a systematic method for the semi-automatic generation of 2.5D models from paintings. Consequently, a number of ad hoc procedures are used to solve most of the typical problems arising when dealing with artistic representation of a scene. Feedbacks provided by a panel of end-users demonstrated the effectiveness of the method in providing models reproducing, using a tactile language, works of art otherwise completely inaccessible.

Keywords: 2.5D model | Minimization techniques | Shape From Shading | Tactile model

Abstract: Design of products characterized by high stylistic content and organic shapes in the form of bas-relief (e.g. fashion accessories, commemorative plaques and coins) is traditionally performed starting from handmade drawings or photographs that are manually reproduced by highly skilled craftsmen such as sculptors and engravers and finally digitized by means of 3D scanning. Several Computer-based procedures have been devised with the aim of speeding up this process, which is considerably time consuming, subjective and costly; these are mainly based on image processing techniques such as embossing, enhancement, histogram equalization or dynamic range, also implemented in CAD-based commercial software. However, these approaches are characterized by several limitations preventing them from providing a "correct" final geometry. In view of that, the present work describes a novel method for the creation of digital bas-reliefs from a single image using a Shape From Shading (SFS) based approach with interactive initialization. Image processing-based techniques and minimization SFS methods are first used in order to retrieve a rough version of the objective surface; successively, this is used as initialization for the final reconstruction algorithm. Tested on a set of case studies, the method proved to be effective in providing satisfactory digital bas-relief from single images. © 2013 © 2013 CAD Solutions, LLC.

Keywords: digital bas-relief | image processing | shape from shading | shape retrieval

Abstract: Texture analysis is an area of intense research activity. Like in other fields, the availability of public data for benchmarking is vital to the development of the discipline. In "Texture databases - A comprehensive survey", Hossain and Serikawa recently provided a precious review of a good number of texture datasets, and put an order into this scattered field. The aim of this appendix is to complement the cited work by providing reference to additional image databases of bio-medical textures, textures of materials and natural textures that have been recently employed in experiments with texture analysis. There is in fact a good number of little-known texture databases which have very interesting features, and for this reason are likely to receive increasing attention in the near future. We are convinced that this extension, along with the original article, will be useful to many researchers and practitioners working in the field of texture analysis. © 2014 Elsevier B.V. All rights reserved.

Keywords: Bio-medical images | Database | Materials | Texture

Abstract: We present a sequential, two-step procedure based on machine vision for detecting and characterizing impurities in paper. The method is based on a preliminary classification step to differentiate defective paper patches (i.e., with impurities) from non-defective ones (i.e., with no impurities), followed by a thresholding step to separate the impurities from the background. This approach permits to avoid the artifacts which occur when thresholding is applied to paper samples that contain no impurities. We discuss and compare different solutions and methods to implement the procedure and experimentally validate it on a datasets of 11 paper classes. The results show that a marked increase in detection accuracy can be obtained with the two-step procedure in comparison with thresholding alone. © 2013 Elsevier B.V. All rights reserved.

Keywords: Image processing | Machine vision | Paper

Abstract: In the aerospace sector, tolerance allocation and inspection of many components must provide not only for ease of manufacturing and cost reduction but also for reliability and safety requirements. Computer Aided Tolerancing and Inspection (CAT&I) methods based on Reverse Engineering techniques may enhance production quality assessment with significant reduction of the time-to-market. This paper presents an original reverse engineering methodology that is being developed to achieve the complete automation of the inspection process starting from the design requirements (dimensional and geometrical tolerances) as they generally appear in the component's official drawings. After a brief presentation of the proposed methodology and its possible implementation oriented to non-planar surface recognition, an aeronautical component made by beta-forging of Ti6Al4V Titanium Alloy powders is presented as test case. The discussion of the procedure allows to point out its benefits in terms of (a) more efficient management of the inspection process and data consolidation; (b) more thorough comprehension of the real component; and (c) a better understanding of possible feedbacks to be applied in design or manufacturing. Finally some remarks about the limits of the proposed methodology are shown and possible enhancements, that have been already planned to be applied, will be described. © 2014 IEEE.

Keywords: beta-forging | Computer Aided Tolerancing and Inspection | Reverse Engineering | Segmentation | Ti6Al4V Titanium Alloy powders

Abstract: The perception of haptic textures depends on the mechanical interaction between a surface and a biological sensor. A texture is apprehended by sliding one’s fingers over the surface of an object. We describe here an apparatus that makes it possible to record the mechanical fluctuations arising from the friction between a human fingertip and easily interchangeable samples. Using this apparatus, human participants tactually scanned material samples. The analysis of the results indicates that the biomechanical characteristics of individual fingertips clearly affected the mechanical fluctuations. Nevertheless, the signals generated for a single material sample under different conditions showed some invariant features. We propose that this apparatus can be a valuable tool for the analysis of natural haptic surfaces.

Keywords: Apparatus | Biomechanics | Biotribology | Humans | Texture

Abstract: Several methods are available for making metal foams. They allow to tailor their mechanical, thermal, acoustic, and electrical properties for specific applications by varying the relative density as well as the cell size and morphology. Foams have a very heterogeneous structure so that their properties may show a large scatter. In this paper, an aluminum foam produced by means of foaming of powder compacts and another one prepared via the infiltration process were analyzed and compared. Image analysis has been used as a useful tool to determine size, morphology, and distribution of cells in both foams and to correlate cell morphology with the considered manufacturing process. The results highlighted that cell size and morphology are strictly dependent upon the manufacturing method. This paper shows how some standard 2D morphological indicators may be usefully adopted to characterize foams whose structure derives from the specific manufacturing process. © 2013 ASM International.

Keywords: aluminum foams | compact powder process | infiltration process | morphometric analysis

Abstract: The space debris represents a danger for operative satellites and human missions. A large amount of debris is located in Low Earth Orbit and in Geostationary Orbit. The worldwide surveillance networks, mainly NORAD and RosKosmos, started monitoring debris since a long a time and testify the continuous growing tendency in the number of objects. Since a few years Aerospace Systems Laboratory of University of Rome started optical space debris observation campaigns by dedicated observatories. The observation activity includes not only planning and taking images of selected portions of the sky, but also analysis of raw picture data to extract the relevant astrometry and/or light-curve information. During the optical campaigns a large amount of images is typically taken and one of the most time consuming activities in optical space objects observation is the data analysis, requiring dedicated and specialized man power. This is the reason why the development of automatic images processing algorithms and procedures to identify the presence of debris, to identify its nature and perform the astrometry computations would highly desirable. This paper deals with the development of automatic procedures and algorithms to detect objects with relative motion with respect to stars in both sidereal tracking mode or terrestrial fixed one. In particular, the developed software is able to recognize the debris inside the picture, solve the star field within the picture and use both these information to achieve the angular measurements of the debris. Relevant efforts have been devoted to software development, such that human interaction is not required. The astrometry computations algorithm works without predefined information about the image. In particular the knowledge of the pointing angles are not required, even if starting from a condition close to the actual one improved the convergence speed, and the picture can be solved starting from a "lost in space" condition. The main algorithm drivers and the tradeoffs in the software implementation are depicted and preliminary results and software performance in actual observation campaigns are discussed in the paper.

Abstract: The space debris is a challenging problem for the human activity in the space. Observation campaigns are conducted around the globe to detect and track uncontrolled space objects. One of the main problems in optical observation is obtaining useful information about the debris dynamical state by the images collected. For orbit determination, the most relevant information embedded in optical observation is the precise angular position, which can be evaluated by astrometry procedures, comparing the stars inside the image with star catalogs. This is typically a time consuming process, if done by a human operator, which makes this task impractical when dealing with large amounts of data, in the order of thousands images per night, generated by routinely conducted observations. An automated procedure is investigated in this paper that is capable to recognize the debris track inside a picture, calculate the celestial coordinates of the image's center and use these information to compute the debris angular position in the sky. This procedure has been implemented in a software code, that does not require human interaction and works without any supplemental information besides the image itself, detecting space objects and solving for their angular position without a priori information. The algorithm for object detection was developed inside the research team. For the star field computation, the software code astrometry.net was used and released under GPL v2 license. The complete procedure was validated by an extensive testing, using the images obtained in the observation campaign performed in a joint project between the Italian Space Agency (ASI) and the University of Bologna at the Broglio Space center, Kenya. © 2014 IAA. Published by Elsevier Ltd. All rights reserved.

Keywords: Automated image analysis | Object detection | Space debris | Star field

Abstract: A system for orbital object monitoring is analyzed, based on a mid-latitude and an equatorial observatory. The enhancements with respect to the use of a single telescope located at mid-latitude, for space debris detection and tracking are highlighted in terms of surveying volume, object identification, and orbital determination accuracy. The need to improve observation capabilities in monitoring and cataloguing such kinds of objects is constantly growing, due to the constant increase of operative satellites and space debris in both geostationary Earth orbit (GEO) and low Earth orbit (LEO) regions. After the considerations on the feasibility of the whole system, an overview of the observatories' design is sketched, on the basis of previous Italian experience in space debris observation, and taking into account constraints imposed by the instrumentation. In particular the main characteristics of components, software for image analysis and observation methodologies are analyzed and a possible configuration is given, based on the ALMASCOPE observatory realized by the Space Robotics Group at the University of Bologna. This observatory was used for the 2010 test campaign carried out from the Broglio Space Center in Kenya. © 2014 IEEE.

Abstract: A systematic characterisation of the porosity in the bulk and surface regions of a sintered Cr-Mo low alloy steel was carried out using image analysis. Fractional porosity in the different regions varies, mainly due to the scatter of the maximum pore size. A higher porosity is found in the bulk region and lower porosity in the regions that contact the die surface during compaction. The maximum pore size is larger in the bulk region than in the surface layers. The large pores are more irregular. With increasing green density, both the fractional porosity and maximum pore size decrease. The fraction of load bearing section in the bulk and surface regions was calculated from fractional porosity and the shape factor of the pores and compared in the different regions. The load bearing section fraction and the maximum pore size were used to predict tensile and fatigue resistance for different densities. The data from the characterisation of the bulk images can predict tensile strength. For fatigue, where the crack nucleates in the surface regions, the use of bulk data underestimates the fatigue resistance. © 2014 Elsevier Inc.

Keywords: Image analysis | Mechanical properties | Porosity | Sintered steels

Abstract: In this article, a methodology to analyze the shear behavior of aluminum foam with closed cells is proposed. A biaxial load device was expressly designed and the elaboration with digital image correlation technique of the data acquired during the test with a charge coupled device (CCD) camera allowed determining the displacement and strain fields. This procedure made it possible to evaluate the procedure as suitable or not for conducting a shear characterization for metallic foam. The τ-γ curves obtained showed an initial elastic outline followed by the yield plateau, a peak load, and a rapid load drop. © 2014 Copyright Taylor & Francis Group, LLC.

Keywords: Aluminum foam | digital image correlation | shear characterization

Abstract: Cultural heritage is often not accessible to visually impaired and blind people, hardly ever when dealing with two-dimensional artworks like, for instance, paintings. In fact, despite tactile reproductions of 3D works of art such as sculptures or architectural models are quite common, a real barrier between blind people and pictorial artworks still exists, obviously due to their intrinsic 2D format. The translation of paintings into bas-relieves is recognized to be one of the most effective ways for breaking down such a barrier, thus allowing a sensible improvement in blind people's accessibility to this kind of works of art. Moving from these considerations, in this work the authors want to provide a bird's eye view on a new methodology for the semi-automatic generation of tactile 3D models starting from paintings, in particular those characterized by single-point perspective. The proposed method relies on an interactive Computer-based modelling procedure, which is conceived to be simple and effective to use. The procedure, which has been implemented into a prototypal software package, has been effectively used to 'translate' a set of paintings from the Italian Renaissance.

Abstract: Design of new industrial objects characterized by high stylistic content often starts from sketches or images of the product to be, subsequently, represented in a 3D digital form by using CAD software. To speed up this phase, a number of methods for automatic or semi-automatic translation of sketches or images into a 3D model have been devised all over the world also for reverse engineering purposes. When the image shading is a crucial information for recovering the final 3D shape, Fast Marching is recognized to be among the best method to date, especially for frontally illuminated scenes. Unfortunately, such a method cannot be directly applied when object illumination in the considered image is oblique. The present work is aimed to propose a simple, but effective, approach for recovering 3D shape of objects starting from single side illuminated scenes i.e. for solving non-eikonal SFS problems. Tested against a set of case studies, the method proved its effectiveness. © (2014) Trans Tech Publications, Switzerland.

Keywords: Digital design | Fast marching | Intelligent manufacturing | Oblique illumination | Shape from shading

Abstract: In the last years the development of interactive Computer-based methods for building virtual and physical 2.5D models from single shaded images faced with an exponential growth. In particular, a wide range of methods based on image processing-based procedures and on Shape From Shading (SFS) can be documented. On the basis of the most favorable techniques devised in literature, the present work describes an improved interactive method capable of retrieving 2.5D models using image shading information. The pro-posed method performs a SFS-based reconstruction where (1) the overall geometry of the expected surface is first recovered and (2) the final 2.5D reconstruction is obtained by minimizing a suitable functional using the rough surface as an initialization function. The method improves previous interactive works by introducing a novel two-step rough surface recovery and a new definition of a functional to be minimized for solving the SFS problem. Tested against a set of case studies the proposed method proves to be effective in providing 2.5D models. © 2014 Science Publications.

Keywords: 2.5D model | Image processing | Interactive reconstruction | Minimization | Shape from shading

Abstract: The visual appearance of seamless dyed edges of luxury leather goods represents a key issue in terms of quality grading since a high-quality leather has to be characterised by homogeneously coloured and shaped edges with uniform ink thickness. Despite a huge literature produced by scientific and technical community to automate many leather manufacturing processes, since leather patches are often characterised by a free-form shape, any attempt of automating leather edges dyeing produced unsatisfactory and inaccurate results. In order to overcome the drawbacks of the existing approaches, the main objective of the present work is to provide a computer-based system for automatically dyeing leather patches edges. The described system includes: 1) a machine vision (MV) hardware equipment, consisting of both illumination and a high resolution acquisition device, devoted to patches edge detection; 2) a pantograph whose dyeing tool is moved along leather edges; 3) a series of computer-based methods for the automatic extraction of the leather patches outlines. Extensive testing performed using the developed machine demonstrated its effectiveness in delivering fast, automatic and high quality edge finishing in a reliable and repeatable way. © 2014 Inderscience Enterprises Ltd.

Keywords: Leather dyeing | Machine vision | Process automation

Abstract: Over the last few years, technologies like 3D scanning and rapid prototyping provided an extraordinary boost in improving reproductions of 3D artworks, like sculptures and historical buildings, all over the world. Physical 3D reproduction of subjects represented in paintings, is recognised to be one of the best ways to allow visually impaired people to enjoy such kind of artworks. However, the use of advanced technologies with the aim of realising 3D models starting from paintings has not been satisfactorily investigated yet. Though a number of algorithms coming from computer vision science exist to cope with similar issues, the specific problem of producing a 3D representation which is targeted at blind people tactile exploration has been only marginally investigated. Starting from these considerations, this work presents 1) a quite extensive review of the criteria proposed in literature for producing tactile models suitable for blind people and 2) four alternative computer-based methods for semi-automatic generation of tactile 3D models starting from RGB digital images of paintings. The outcomes of this study contribute new information to the field of visually impaired user-oriented 3D reconstruction and clearly indicate the strategy to be adopted in order to produce a meaningful reproduction of a bi-dimensional piece of artwork. © 2014 Inderscience Enterprises Ltd.

Keywords: 3D computer-based modelling | Blind | Haptic exploration | Visually impaired

Abstract: Wheel alignment, consisting of properly checking the wheel characteristic angles against vehicle manufacturers' specifications, is a crucial task in the automotive field since it prevents irregular tyre wear andaffects vehicle handling and safety. In recent years, systems based on Machine Vision have been widely studied in order to automatically detect wheels' characteristic angles. In order to overcome the limitations of existing methodologies, due to measurement equipment being mounted onto the wheels, the present work deals with design and assessment of a 3D machine vision-based system for the contactless reconstruction of vehicle wheel geometry, with particular reference to characteristic planes. Such planes, properly referred to as a global coordinate system, are used for determining wheel angles. The effectiveness of the proposed method was tested against a set of measurements carried out using a commercial 3D scanner; the absolute average error in measuring toe and camber angles with the machine vision system resulted in full compatibility with the expected accuracy of wheel alignment systems. © 2013 Furferi et al.

Keywords: Machine vision | Stereovision | Wheel alignment

Abstract: Automatic detection and assessment of dirt particles in pulp and paper plays a pivotal role in the papermaking industry. Traditional visual inspection by human operators is giving the way to machine vision, which provides many potential advantages in terms of speed, accuracy and repeatability. Such systems make use of image processing algorithms which aim at separating paper and pulp impurities from the background. The most common approach is based on image thresholding, which consists of determining a set of intensity values that split an image into one or more classes, each representing either the background (i.e.: An area with no defects) or an area with some types of contraries. In this paper we present a quantitative experimental evaluation of four image thresholding methods (i.e.: Otsu's, Kapur's, Kittler's and Yen's) for dirt analysis in paper. The results show that Kittler's method is the most stable and reliable for this task. © 2013 DIME UNIVERSITÀ DI GENOVA.

Keywords: Image thresholding | Machine vision | Paper | Quality assessment

Abstract: Foams and porous materials with cellular structure have many interesting combinations of physical and mechanical properties coupled with low specific weight. By means of replication casting it is possible to manufacture foams from molten metal without direct foaming. A soluble salt is used as space holder, which is removed by leaching in water. This can be done successfully if the content of space holding fillers is so high that all the granules are interconnected. One of the main advantages of using the replication casting is a close control of pore sizes which is given by the distribution of particle sizes of the filler material. This contrasts with the pore size distribution of the materials foamed by other processes where a wider statistical distribution of pores is found. On the other hand, the maximum porosities that can be achieved using space holders are limited to values below 60%, whereas the other methods allow for porosities up to 98%. Temperature of the mould and infiltration pressure are critical process parameters: a typical problem encountered is the premature solidification of the melt, especially due to the high heat capacity of the salt. In this work foam properties such as cell shape, distribution and anisotropy and defect presence are investigated by using digital image processing technique. For this purpose replicated AlSi7Mg0.3 alloy foams are produced by infiltrating preforms of NaCl particles, varying the metal infiltration pressure and the mould preheating temperature. An original procedure based on image analysis has been set up to determine size, morphology and distribution of cells. The paper demonstrates that this methodology, coupled with microstructural analysis, is a useful tool for investigating the effects of process parameters on foam properties.

Keywords: Aluminium foams | Foam morphology | Image analysis | Replication casting | Watershed method

Abstract: 3D topological segmentation entails the partition of 3D clouds of connected voxels (e.g. 3D images) into sets of entities, connected by a series of nodes. Especially for thread-like structures (e.g. blood vessels, proteins, piping and voxel-based 3D sketches), nodes detection and, more in particular, identification of entities converging in a node may be considered a crucial issue to correctly interpret the "structure" of the analysed object. The main objective of the present work is to describe an innovative algorithm able to determine the possible intersection zones between groups of voxels composing a thread-like 3D voxel cloud. The devised algorithm is based on a multi-directional ray-tracing procedure applied, for each voxel of the 3D dataset, with reference to a set of directions defined by an appropriate 3D neighbourhood domain. The thread-like structure thicknesses, coming from the ray-trace analysis, are estimated along different directions. Finally, the set of thicknesses is analysed by means of a statistical approach so that voxels, possibly belonging to intersection zones, can be identified. The proposed algorithm demonstrated its effectiveness in a number of test cases. Copyright © 2013 Binary Information Press.

Keywords: 3D topology | Local thickness | Ray-trace analysis | Voxel graphics

Abstract: Furniture glass tiles are increasingly used for covering walls and facades or for conferring fashionable aesthetical properties to buildings. Companies that produce furniture glass tiles of a desired colour are devoted to performing a colour comparison between the manufactured glass tiles and the ones desired by a customer, or provided by a catalogue. Still today, such a comparison, known as 'colour matching', is mainly performed by company experts by means of a visual inspection, thus leading to a subjective and qualitative colour assessment. A number of methods for colour matching have been afforded in the literature in several industrial fields such as textile, plastics or food; unfortunately, to the best of author's knowledge, no practical method for glass tiles colour matching has been devised until today. The present work provides an image processing-based method capable of carrying out nonpatterned glass tiles colour matching. The method is devised using an appositely developed hardware so as to extract a series of statistical data from scanned images of 10 mm sized glass tiles and, on the basis of the definition of two novel colour distance formulas, endows with colour matching. The achieved colour matching performance agrees in 91% of tests with expertperformed colour classification. The provided formulas are meant to be of general usage for assessing glass tiles colour matching. © RPS 2013.

Keywords: Colour gaussian | Colour matching | Glass | Image processing | Mahalanobis

Abstract: Minimisation techniques are commonly adopted methodologies for retrieving a 3D surface starting from its shaded representation (image), i.e., for solving the widely known shape from shading (SFS) problem. Unfortunately, depending on the imaged object to be reconstructed, retrieved surfaces often results to be completely different from the expected ones. In recent years, a number of interactive methods have been explored with the aim of improving surface reconstruction; however, since most of these methods require user interaction performed on a tentative reconstructed surface which often is significantly different from the desired one, it is advisable to increase the quality of the surface, to be further processed, as much as possible. Inspired by such techniques, the present work describes a new method for interactive retrieving of shaded object surface. The proposed approach is meant to recover the expected surface by using easy-to-set boundary conditions, so that the human-computer interaction primarily takes place prior to the surface retrieval. The method, tested on a set of case studies, proves to be effective in achieving sufficiently accurate reconstruction of scenes with both front and side illumination. © 2013 Inderscience Enterprises Ltd.

Keywords: Boundary conditions | Computational vision | Human-computer interaction | Minimisation techniques | SFS | Shape from shading

Abstract: Multispectral imaging techniques are widely used to analyse and restore digital images of ancient documents degraded over time. In particular, acquisitions in infrared and ultraviolet bands can reveal information invisible by naked eye, which is not captured by conventional RGB imaging. Multispectral acquisitions are usually performed with filter-wheel cameras that mount a series of interference filters in front of the sensor to select the spectral band in which the document has to be acquired. Due to the use of different filters, the focus of the lens changes and it is necessary to adjust it manually for each filter, because such imaging systems are devoid of automatic focusing. Thus the acquired images may not be perfectly in-focus and have misalignments. In this work we present an automatic solution to acquire a multispectral data cube of aligned images that can be used in document analysis to extract and/or separate information through enhancement techniques. A custom-made motorized autofocus system controlled by software has been installed on a filter-wheel camera, which allows us to acquire in-focus images automatically at each filter changing, and a registration method based on Fourier-Mellin transform aligns these images. A preliminary calibration is performed to set the focusing of each filter with the working distance. As a result, the camera can capture images independently from the contrast of the scene, also in presence of documents with homogeneous texture. The proposed solution reduces considerably the acquisition time and offers a tool to acquire automatically the data cube to be used in further image analysis techniques. The results of experimentations are hereby presented and discussed. © 2012 Elsevier Masson SAS.

Keywords: Document analysis | Focusing | Image registration | Multispectral imaging

Abstract: This paper is about the development of an expert system for automatic classification of granite tiles through computer vision. We discuss issues and possible solutions related to image acquisition, robustness against noise factors, extraction of visual features and classification, with particular focus on the last two. In the experiments we compare the performance of different visual features and classifiers over a set of 12 granite classes. The results show that classification based on colour and texture is highly effective and outperforms previous methods based on textural features alone. As for the classifiers, Support Vector Machines show to be superior to the others, provided that the governing parameters are tuned properly. © 2012 Elsevier Ltd. All rights reserved.

Keywords: Classification | Colour | Grading | Granite | Texture

Abstract: The actual foam density affects its mechanical energy absorption capabilities. Making structural elements starting from the cutting of semi-finished items may produce uneven results due to the lack of homogeneity in the foam. The subject of this work is the study of AlSi7 metallic foams, the focus being on the evaluation of the effective density distribution throughout large ingots. This is the first step required to establish a correlation between manufacturing process parameters and mechanical properties. The results highlighted that the void density increases from the centre toward the ingot outer wall and that specimens coming from different regions of the ingot have a very different mechanical behaviour. This is probably due to the difficulty in controlling temperature gradients and cooling rates throughout big mould cavities during the production process. © 2012 Elsevier B.V.

Keywords: Aluminium alloy foams | Cellular materials | Mechanical characterisation

Abstract: Yarn hairiness and yarn hand represent key parameters to be strictly assessed and controlled in textile processes since they affect many aspects such as visual appearance of yarns (and consequently of fabrics), handle, thermal insulation, pleasant sensation during touch and smoothness. This is particularly true when fancy yarns, such as jaspè or frisè, are produced using ring spinning: colored natural fibers composing the fancy yarns are required to protrude, to some extent, from the yarn core, usually composed by synthetic material, so as to impart the desired properties in terms of smoothness and luster. With the aim of realizing highest performing fancy yarns, a novel ring spinning system, equipped with a double drafting unit, has been realized by Università di Firenze thanks to the contribute of Tuscany Region (Italy). Once the fancy yarns are obtained, the performance of this innovative ring spinning is evaluated by means of a Computer Aided analysis of yarn geometry able to provide a novel measurement of yarn hairiness and to quantitatively define a yarn hand-related parameter. A Machine Vision system has been devised in order to acquire yarn geometry so that an accurate analysis can be carried out. Such computer aided-based analysis allows to determine two parameters used for determining hairiness and hand: the "equivalent yarn hairiness" and the "yarn hand index". Such parameters are evaluated for yarns obtained using both the innovative and a conventional ring spinning machine so that the yarns quality can be effectively compared. Based on the obtained results that the proposed method proved to be suitable and effective for evaluating yarn hairiness within an average error of about 5.40% with respect to the Uster tester. Furthermore, a good correlation (93%) between objective and subjective assessment of yarn hand was reached.

Keywords: Computer Aided analysis | Image processing | Yarn geometry | Yarn hairiness | Yarn hand

Abstract: The fatigue behaviour is examined in terms of calorimetric effects. Aluminum alloy and steel have been chosen as reference materials. Heat sources accompanying the fatigue mechanisms are derived from thermal images provided by an infrared camera. A processing method allows identifying separately thermoelastic and dissipative sources. Thermoelastic effects are compared to theoretical predictions given by the basic, linear, isotropic thermoelastic model. Dissipation amplitudes are analyzed as a function of the loading frequency and stress amplitude applied to the fatigue specimen. Finally, the heterogeneous character of the fatigue development is studied both in terms of thermoelastic and dissipation sources.

Abstract: Current research on underwater 3D imaging methods is mainly addressing long range applications like seafloor mapping or surveys of archeological sites and shipwrecks. Recently, there is an increasing need for more accessible and precise close-range 3D acquisition technologies in some application fields like, for example, monitoring the growth of coral reefs or reconstructing underwater archaeological pieces that in most cases cannot be recovered from the seabed. This paper presents the first results of a research project that aims to investigate the possibility of using active optical techniques for the whole-field 3D reconstructions in an underwater environment. In this work we have tested an optical technique, frequently used for in air acquisition, based on the projection of structured lighting patterns acquired by a stereo vision system. We describe the experimental setup used for the underwater tests, which were conducted in a water tank with different turbidity conditions. The tests have evidenced that the quality of 3D reconstruction is acceptable even with high turbidity values, despite the heavy presence of scattering and absorption effects. © 2011 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

Keywords: 3D reconstruction | Imaging in turbid medium | Photogrammetry | Structured light | Underwater imaging

Abstract: Chronic wounds represent a particular debilitating health care problem, mainly affecting elderly people. A full and correct diagnosis of tissue damage should be carried out considering both dimensional, chromatic, and thermal parameters. A great variety of methods have been proposed with the aim of producing objective assessment of skin lesions, but none of the existing technologies seem to be robust enough to work for all ulcer typologies. This paper describes an innovative and non-invasive system that allows the automatic measurement of non-healing chronic wounds. The methodology involves the integration of a three-dimensional (3D) optical scanner, based on a structured light approach, with a thermal imager. The system enables the acquisition of geometrical data, which are directly related to chromatic and temperature patterns through a mapping procedure. Damaged skin areas are detected by combining visible and thermal imaging. This approach allows for the automatic measurement of extension and depth of ulcers, even in the absence of significant and well-defined chromatic patterns. The proposed technology has been tested in the measurement of ulcers on human legs. Clinical tests have demonstrated the effectiveness of this methodology in supporting medical experts for the assessment of chronic wounds. © 2011 Authors.

Keywords: 3D model reconstruction | 3D thermography | image processing | wound assessment

Abstract: Automatic on-line signature recognition has been investigated by several authors in order to allow machines to recognize an user from its own biometric traits. The following paper deals with features and models required in order to allow a machine to learn and discriminate signatures. The proposed solution approaches the signature making process as the motion of a point in a bi-dimensional space and model s statistic properties of the motion via the well known Maximum a Posteriori training of Gaussian Mixture Models. Comparing our approach to state-of-the-art solutions, major advancements have been found. As first, both system accuracy in signature discrimination and system resistance to forgeries have been double. Eventually, the proposed modeling technique leads to smaller templates, whose size is halved with respect to state-of-theart alternatives.

Keywords: Biometry | Maximum a posteriori | On-line signature recognition | Pattern recognition

Abstract: The evolution of olive oil technology is related to research raised to deepen the understanding of biological and biophysical phenomena during the machining process olives, thus allowing the introduction of sensors able to monitoring the parameters and the process according to the characteristics of olives themselves. Current research has identified manufacturing protocols that can enable the achievement levels of product quality required by the market, mainly by reducing the time between collection and processing of olives and raising the technological level of extraction lines. In this context, the present paper aims to describe some of the results of a three-years project developed by the PIN-University of Florence (Italy) in collaboration with the Tuscan Regional Agricultural Development, the Florence Commerce Chamber "Laboratorio Chimico Merceologico-Azienda Speciale CCIAA di Firenze" and the SME "TEM" (Toscana Enologica Mori). The paper will describe the development of an innovative Machine Vision system able to 1) acquire, in real-time, images of olives in the conferring phase and 2) to process the acquired images in order to evaluate the ripeness of olives on the basis of their colour and the eventual presence of superficial defects. The devised system has been tested with the data extracted by olives in the harvesting period of year 2006. © 2011 by Nova Science Publishers, Inc. All rights reserved.

Abstract: Automatic on-line signature identification is a procedure which allows a machine to identify a subject among a cohort of individuals by using only the subject's signature. The following paper deals with features and models required in order to allow a machine to learn and discriminate people on the basis of such a biometric trait. The proposed solution presents a neural network based framework for template adaptation which has demonstrated to improve the resilience of a system, when it has to face with forgeries, that is, fake signatures which are used in order to attack the system and grant unauthorized access to services. The proposed framework provides an improved security level of 35% with respect to non adapted systems.

Keywords: Adaptation | Artificial neural networks | Identification | Signature

Abstract: It is well-known that local binary pattern (LBP) histograms of real textures exhibit a markedly uneven distribution, which is dominated by the so-called uniform patterns. The widely accepted interpretation of this phenomenon is that uniform patterns correspond to texture microfeatures, such as edges, corners, and spots. In this paper we present a theoretical study about the relative occurrence of LBPs based on the consideration that the LBP operator partitions the set of grayscale patterns into an ensemble of disjoint multidimensional polytopes. We derive exact prior probabilities of LBPs by calculating the volume of such polytopes. Our study puts in evidence that both the uneven distribution of the LBP histogram and the high occurrence of uniform patterns are direct consequences of the mathematical structure of the method rather than an intrinsic property of real textures. © 2011 Springer Science+Business Media, LLC.

Keywords: Local binary patterns | Polytopes | Texture

Abstract: Nowadays three-dimensional Computer Aided modeling is of out-standing importance in the mechanical design process since it impacts on several issues like visualization, simulation, machining, etc. Anyway, multi orthographic view engineering drawings have been widely used up to latest decade and still are, so they play an essential role in traditional engineering. The conversion from 2D drawings to 3D CAD models is still a key task in a wide range of applications. In order to cope with this issue a number of works have been proposed in the last decades, providing a series of methodologies for solving the reconstruction prob-lem. On the basis of such methodologies the main aim of the present paper is to suggest a comprehensive, orderly, unambiguous and automatic procedure meant to help researchers and practitioners who want to deal with the reconstruction problem. The procedure, by using an appropriate formal mathematic language, systematize and integrates some of the methods proposed so far. © 2011 Heldermann Verlag.

Keywords: 3D reconstruction | Computational geometry | Computer aided design | Engineering drawings | Or-thographic projections | Pseudo-wireframe

Abstract: Marbling effect on fabrics is a relevant aesthetic feature, increasing its diffusion specially in the field of textiles for technical applications. The fabric aesthetic anisotropy, characterizing the marbling effect, has a strong impact on the perceived quality: a high-quality marbled fabric to be used in automotive textiles, for instance, is characterized by a tiny quantity of veins and spotted areas. A large amount of "veins" and/or discolored areas may induce a customer to consider the fabric as "defected". In common practice, the identification of whether the fabric is defective or not is performed by human experts by means of visual inspection. As a consequence, fabric inspection is performed in a qualitative and unreliable way; thereby the definition of a method for the automatic and objective inspection is advisable. On the basis of the state of the art, the present work aims to describe a computer-based approach for the automated inspection of marbling effect on fabrics, resulting in the classification of fabrics into three quality classes. The devised apparatus is composed by a machine vision system provided with an image processing-based software. The processing software is able to determine the anisotropy of a fabric using edge segmentation and image entropy and defining a "fabric entropy curve" The proposed method proves to be able to classify the fabrics into the correct quality class in 90% of the cases, with respect to the selection criteria provided by human operators.

Keywords: Artificial vision | Edge detection | Fabric inspection | Image entropy | Marbling effect

Abstract: Digital applications such as CG, CAD and GIS are based on vectorial data since all the information about shape, size, topology etc. are provided in such kind of data representation rather than raster one. Turning raster images into vector ones is a key issue which has been addressed by a number of authors but still far to be exhaustively worked out. Especially in the case of 2D images representing technical drawings, fitting analytical curves to point clouds (pixel sets) is a critical matter. The present paper provides a novel approach to fit unordered point cloud data. Such an approach integrates a PCA-based method, for detecting the main local directions of the point cloud and to order the points, with and a weighted approximation of a B-spline curve to the original data, based on pixel gray levels. The methodology, tested against alternative techniques based on Least Square (LS) B-spline approximation and on image thinning, proved to be effective in preserving the original shape according to human perception.

Keywords: Curve reconstruction | Image processing | PCA | Unorganized points | Weighted least-squares

Abstract: One of the most critical phases of the production of carded fiber is the comparison between the colour of the finished product and the colour desired by a customer or provided in a catalog. In most cases, the required proportions of coloured fibers for obtaining a desired final colour of a fiber are evaluated by trial and error techniques. This approach, which often lacks a computer-aided tool to assist colourists, allows the assessment of a recipe to reproduce a target colour. The companies producing carded fibers often perform a colorimetric control of their product. This is obtained by evaluating the colorimetric distance between the final product, obtained by mixing some coloured raw fibers in order to obtain a homogeneous colour, and the desired one. When this colorimetric distance exceeds a value stated by the customer, the companies have to modify the recipe in order to reduce the gap between the colour of the final product and the desired one. The present work describes a novel approach for a reliable prediction of the spectrophotometric response of a carded fiber based on the spectrophotometric response of the raw materials composing the fiber itself. This is obtained for any variation of an original recipe. The developed system is, first, based on a theoretical approach used for the prediction of reflectance factors obtained by mixing the same kind of differently coloured raw material. A more general approach, based on Artificial Neural Networks (ANNs), is then described. This second approach performs a reliable prediction of the reflectance factors of a carded fiber composed by several kind of differently coloured raw materials. The two approaches were used to predict the reflectance factors of 500 different blends. Colour differences between the predicted reflectance factors and the real spectrophotometric response of the carded fibers are measured and expressed in CIELAB and CMC(2:1) distances under several standard illuminants. Referring to the test performed in the present work, the mean predicted colour difference in terms of CIELAB is less than 0.24. The maximum distance in terms of CMC(2:1) is less than 0.25. Experimental validation demonstrates that the proposed approach is suitable for a reliable, fast and practical prediction of the recipes for carded fibers. For these reasons, the developed system is actually running into the Laboratory of an important textile company located in Prato (Italy): the New Mill S.p.A. © 2010 Wiley Periodicals, Inc.

Keywords: artificial neural network | carded fiber | spectrophotometry

Abstract: An automatic 3D model retrieval from freehand conceptual sketches is a key target for both commercial software houses and academic research. Unfortunately, most of the approaches are not suitable for properly translating stylistic sketches into 3D models. In order to carry out this 3D model conversion, the first task to be dealt with is to turn raster data (3D or 2D free-form curves) into vectorial ones. Such a task represents a key issue which has been addressed by a number of authors but still far to be exhaustively worked out. To address this challenge, this work presents a new method that allows to fit 2D unordered point cloud data with Multiple Incident Splines (MISs). At the heart of the proposed approach are two main procedures: the first one is based on Euclidean Minimum Spanning Tree (EMST) and Principal Component Analysis (PCA) for detecting the main local directions of the point cloud and to order its points while preserving original topology; the second is meant to fit ordered point clouds with spline curves providing a robust intersection and vertex detection. The proposed methodology, tested on a number of case studies, proves to preserve the original topology more efficiently than alternative techniques supplied by commercial vectorization software packages.

Keywords: Curve reconstruction | Freehand sketches | Image Processing | Styling | Unorganized point cloud

Abstract: Car seat fabrics are uniquely fashioned textiles. A number of them is branded by a sponged-like appearance, characterized by spots and slightly discoloured areas. Their surface anisotropy is considered to be a relevant aesthetic feature since it has a strong impact on customer perceived quality. A first-rate car seat fabric requires a "small" quantity of spots and discoloured areas while fabrics characterized either by a large number or by a low number of spots, are considered to be of lower quality. Therefore, car seat fabric quality grading is a relevant issue to be dealt with downstream to the production line. Nowadays, sponged-like fabric grading is performed by human experts by means of manual inspection and classification; though this manual classification proves to be effective in fabric grading, the process is subjective and its results may vary depending on the operator skills. Accordingly, the definition of a method for the automatic and objective grading of sponged-like fabrics is necessary. The present work aims to provide a computer-based tool capable of classifying sponged-like fabrics, as closely as possible to classifications performed by skilled operators. Such a tool, composed by an appositely devised machine vision system, is capable of extracting a number of numerical parameters characterizing the fabric veins and discoloured areas. Such parameters are, then, used for training an Artificial Neural Network (ANN) with the aim of classifying the fabrics in terms of quality. Finally, a comparison between the ANN-based classification and the one provided by fabric inspectors is performed. The proposed method, tested on a validation set composed by 65 sponged-like fabrics, proves to be able to classify the fabrics into the correct quality class in 93.8% of the cases, with respect to the selection provided by human operators.

Keywords: Artificial neural networks | Car seat fabrics | Grading | Machine vision

Abstract: Classification of wasted woollen textiles on the basis of their colour is a basic approach for the supply of a raw material which does not involve the cost of the colouring process. Colour classification is a very difficult task, especially when a fabric is composed by differently coloured fibre (melange fabric). Many systems have been developed in the last years for colour classification of textiles. Unfortunately such colour classification systems are not able to correctly classify melange fabrics. In the present work a method for real-time classification of melange colour woollen fabrics is proposed. The provided approach, that is suitable also for classifying solid colour fabrics, integrates a Machine Vision (MV) system, able to acquire high resolution images, with a clustering algorithm capable of mapping the colour pixel of fabric images into a series of colour classes. The proposed system provides a colour classification with a misclassification less than 10% when compared with the classification resulting from apanel of expert human operators. A comparison between the proposed method and some tools stated in scientific literature is also afforded. © 2011 Asian Network for Scientific Information.

Keywords: Machine vision | Mapping | Melange | Recycling | Textiles

Abstract: In the field of 3D scanning, there is an increasing need for more accurate technologies to acquire 3D models of close range objects. Underwater exploration, for example, is very hard to perform due to the hostile conditions and the bad visibility of the environment. Some application fields, like underwater archaeology, require to recover tridimensional data of objects that cannot be moved from their site or touched in order to avoid possible damages. Photogrammetry is widely used for underwater 3D acquisition, because it requires just one or two digital still or video cameras to acquire a sequence of images taken from different viewpoints. Stereo systems composed by a pair of cameras are often employed on underwater robots (i.e. ROVs, Remotely Operated Vehicles) and used by scuba divers, in order to survey archaeological sites, reconstruct complex 3D structures in aquatic environment, estimate in situ the length of marine organisms, etc. The stereo 3D reconstruction is based on the triangulation of corresponding points on the two views. This requires to find in both images common points and to match them (correspondence problem), determining a plane that contains the 3D point on the object. Another 3D technique, frequently used in air acquisition, solves this point-matching problem by projecting structured lighting patterns to codify the acquired scene. The corresponding points are identified associating a binary code in both images. In this work we have tested and compared two whole-field 3D imaging techniques (active and passive) based on stereo vision, in underwater environment. A 3D system has been designed, composed by a digital projector and two still cameras mounted in waterproof housing, so that it can perform the various acquisitions without changing the configuration of optical devices. The tests were conducted in a water tank in different turbidity conditions, on objects with different surface properties. In order to simulate a typical seafloor, we used various concentrations of clay. The performances of the two techniques are described and discussed. In particular, the point clouds obtained are compared in terms of number of acquired 3D points and geometrical deviation.

Keywords: Dense reconstruction | Stereo vision | Structured-light | Underwater imaging

Abstract: This paper presents a new 3D design paradigmfor the development of specific custom-fit products, such as the soft socket of prostheses for lower limb amputees. It is centered on the digitalmodel of the human body and, contrarily to the traditional process almost manually based, it considers the integration of methods and tools coming from different research and application fields: Reverse Engineering, Medical Imaging, Virtual Prototyping, Physics-based Simulation, and Rapid Prototyping. The paper describes the techniques adopted to acquire and create the digital model of the residual limb, the procedure to generate the socket model, the strategy developed for the functional simulation of the socket-stump interaction and, finally, the realization of the physical prototype. Each design step is described with the related problems and the obtained results. Both trans-tibial and trans-femoral amputees have been considered; however, for now the complete process has been validated for trans-tibial prostheses. Major outcomes of the proposed approach stand in a better quality of the final product, in a shorter involvement of the amputee implying a lower psychological impact, in a limited use of physical prototypes, and in a shorter development time. Moreover, the resulting paradigm answers to the Collaborative Engineering guidelines by optimizing the interaction between different domains and enhancing their contributions in a homogeneous development framework. © 2010 Elsevier B.V. All rights reserved.

Keywords: Custom-fit products | Human-centric soft product design | Physics-based modeling for soft products | Prosthesis development process

Abstract: Color match prediction is one of the most important aspects to be considered by industries dealing with colorants. Several generally applicable theoretical models have been proposed so far for helping the colorists in achieving an exact color match. Such approaches, often based on extensive experimental tests and provided of exhaustive results, are differentiated by a specific range of application (textiles, study, paintings, etc.). Therefore, the results are subjected to restrictions or constraints (number of colorants, reliability of the prediction, etc.). The present paper describes, into a mathematical form, three widely known techniques adopted in the scientific literature for evaluating the spectrophotometric color match prediction of a target shade: Kubelka-Munch, Steams-Noechel and Artificial Neural Networks. The proposed method starts from such wide known methodologies and by means of mathematical assessment provides some useful equations to be straightforwardly used for color matching. Moreover an Artificial Neural Network based formulation is provided. The results of the work shows that the expected color distance between the predicted the real color of a shade is less than 0.8, in terms of CTEL*a*b* distance. © 2010 Asian Network for Scientific Information.

Keywords: Absorptivity and the scattering | Color distance | Color formulation | Color matching transfer function | Reflectance

Abstract: The color and the color stability of a fabric dyed with a jigger machine are highly dependent on the color of the dyes and on technological parameters, such as the process temperature, pH of the dyebath, and time of dyeing. On the basis of their skill, colorists are capable of choosing the technological parameters and the recipes for dyes in order to obtain the desired dyed fabric. However, they need to perform many tests before reaching the preferred product. As a matter of fact, a straightforward relationship between the color of dyes, process parameters, and final color and color solidity is not found in literature. The present work aims to help the colorist in predicting the color and the color stability of the fabric, without the needing to physically dye it. In detail the paper describes a tool, based on the Cascade Neural Network (CNN), that is able to receive the value of some colorimetric and technological parameters as input and to predict, as output, the color appearance and the color solidity of a fabric dyed with a jigger machine. The CNN is composed of a “color prediction module” (ANN I) and a “color solidity prediction module” (ANN II) that work in cascade. The CNN has been validated by means of a large set of experiments. The mean error between the color prediction and the real values of the dyed fabric, in terms of CIE 1976 (L*, a*, b*) color distance, is equal to 0.47 with a variance of 0.031. The maximum color solidity prediction error is 0.5. © 2010, SAGE Publications. All rights reserved.

Abstract: In this paper we study the feasibility of developing a search engine capable of retrieving images from a granite image database based on a query image that is similar to the intended targets. The main focus was on the determination of the set of colour and/or texture features which yields highest retrieval accuracy. To assess the performance of the considered image descriptors we created a granite image database, formed by images recorded at our laboratory as well as taken from the Internet. Experimental results show that colour and texture features can be successfully employed to retrieve granite images from a database. We also found that improved accuracy is achieved by combining different colour and texture feature sets through classifier fusion schemes.

Keywords: CBIR | Colour | Granite | Image retrieval systems | Texture | Visual appearance

Abstract: The influence of ripening degree of drupes during the harvesting period is well established in olive oil sector. A range of methods for expressing the stage of maturity of olives have been proposed in scientific literature. One of the most commonly adopted methods provides the evaluation of a Ripening Index (RI) on the basis of olive skin and pulp colour. Unfortunately, the RI evaluation technique is time-consuming, subjective (depending on expert skill) and depends on environmental conditions that may affect colour appearance of olives. This work describes a novel method for rapid, automatic and objective prediction of the Ripening Index of an olive lot. The method integrates a Machine Vision system, capable of performing a colour-based raw prediction of RI, with an Artificial Neural Network (ANN) based algorithm to refine it. Such a refinement is based on a set of chemical parameters (oil content, sugar content and phenol content) which are provided as input to the ANN and which can be obtained by historical curves for the region where the RI needs to be predicted. Experimental results demonstrate the effectiveness of the proposed approach. © 2010 Elsevier Ltd. All rights reserved.

Keywords: Artificial neural networks | Machine vision system | Ripening index

Abstract: Two different closed-cell aluminium foams, manufactured by compact powder technology starting from 7075 and 6061 alloys, were studied with the aim of investigating the effect of heat treatments on their axial crushing behaviour. By means of scanning electron microscopy/energy-dispersive spectroscopy analyses, the crushing response was investigated in an attempt to understand how heat treatments may improve the absorbing efficiency of crashboxes. © 2009 Acta Materialia Inc.

Keywords: Aluminium alloy | Aluminium foam | Crashworthy design | Heat treatment | Microstructure

Abstract: Three different aluminium foams, manufactured by compact powder technology starting from 7075, 6061 and AlSi7 alloys were studied by performing microstructural and morphometric analyses, with the aim of explaining their different behaviour during axial crushing. Void distribution coupled with material microstructure justifies the behaviour of load-displacement curves obtained during axial crushing of the foams. The results show that 7075 alloy seems to be the material having the best behaviour during crushing, at least when the foam is removed of the external walls. Despite that outer skin presence coupled with the intrinsic brittle behaviour of this alloy may cause instability, if it is used to fill hollow components like crashboxes. During deformation process 6061 and AlSi7 alloys that are more ductile, give in and maintain contact adapting to the encasement deformation. © 2007 Elsevier B.V. All rights reserved.

Keywords: Aluminium alloy | Aluminium foam | Crashworthy design | Heat treatment | Microstructure

Abstract: Recycling of clothes is a straightforward approach for the supply of a coloured raw material which does not involve the cost of the colouring process. A real time and completely automated colour classification tool for woollen clothes to be recycled is proposed. The tool uses the combination of a statistical method, called matrix approach, of a self-organizing feature map (SOFM) and a feed-forward backpropagation artificial neural network (FFBP ANN)-based approach, to correctly classify the clothes by respecting the selection criteria provided by human know-how. The developed tool, which uses an appositely developed workbench with a spectrophotometer, is aware of the way the different coloured clothes to be recycled combine each other to create a new one. The tool has been validated using a set of 5,000 differently coloured clothes to be recycled and the classification error in classifying the clothes is within 5%, i.e., lower than the one resulting from the use of an expert human operator. © 2007 Springer-Verlag London Limited.

Keywords: Colour | Neural networks | Picking | Recycling | Spectrophotometry

Abstract: This work describes an automated artificial vision inspection (AVI) system for real-time detection and classification of defects on textile raw fabrics. The tool (software + hardware) is directly attached to an appositely developed appraisal equipment machine (weave room monitoring system) and the inspection is performed online. The developed tool performs (1) the image acquisition of the raw fabric, (2) the extraction of some critical parameters from the acquired images, (3) an artificial neural network (ANN)-based approach able to detect and classify the most frequently occurring types of defects occurring on the raw fabric and (4) a standard image processing algorithm that allows the measurement of the geometric properties of the detected defects. The reliability of the tool is about 90% (defect detected vs. effectively existing defects), that is, similar to the performance obtained by human experts. Once detected the defects are correctly classified in 88% of cases and their geometrical properties are measured with a sub-pixel precision.

Keywords: Artificial neural network | Image processing | Raw fabrics | Real time

Abstract: This work provides a software based on the combination of a artificial neural network (ANN) approach and a numerical method (called "refining algorithm") for the estimation of the acidity level and of peroxides number of olive oil extracted by a continuous extraction process. The estimation is achieved through the measurement of some agronomical and technological parameters commonly measured by the technicians working at the oil mills. The ANN based approach is able to perform a rough prediction of the two parameters; this prediction is then refined by means of the numerical approach. The devised software, developed using a database of experimental data collected in the years 1997-2004 in the Tuscany Region (Italy), is able to estimate the two parameters during the continuous oil extraction, thus allowing a real-time control of the oil quality during the extraction process. The experimental data are related to different kinds of extraction systems: the data collected before 2003 are mainly referred to three phases decanting while the one collected in years 2003-2004, are referred to a two phases decanter. The goal of this approach is to build up a fast and reliable quality control without performing the standard laboratory analysis. The results of the estimation achieved by the ANN based system are compared with the results of the chemical analyses carried out by Florence Commerce Chamber "Laboratorio Chimico Merceologico-Azienda Speciale CCIAA di Firenze" according in force to European Union Rules standards. The mean error in estimation of the parameters with the combination of the ANN approach and the refining algorithm, in comparison with the standard chemical analysis, is in the range 6-8% for an oil extraction with a three phases decanting system and about 6-7% for an oil extraction with a two phases decanting system. The maximum error affecting the method (ANN + Refining) described in this work is about 15% for the first case and about 11% for the second one. The system developed in the present work is actually running on the oil mill "TEM Toscana Enologica Mori" of Florence, Italy. The present work has been financed by the Tuscany Regional Agricultural Development and Innovation Office (ARSIA: Azienda Regionale per lo Sviluppo e l'Innovazione dell'Agricoltura) and is a part of a 3-year project whose objective is to create an entirely software + hardware controlled oil mill. © 2007 Elsevier B.V. All rights reserved.

Keywords: Artificial neural network | Olive oil | Olive oil acidity level | Olive oil centrifugal process | Peroxides number

Abstract: A reliable prediction of ductile failure in metals is still a wide-open matter of research. Several models are available in the literature, ranging from empirical criteria, porosity-based models and continuum damage mechanics (CDM). One major issue is the accurate identification of parameters which describe material behavior. For some damage models, parameter identification is more or less straightforward, being possible to perform experiments for their evaluation. For the others, direct calibration from laboratory tests is not possible, so that the approach of inverse methods is required for a proper identification. In material model calibration, the inverse approach consists in a non-linear iterative fitting of a parameter-dependent load-displacement curve (coming from a FEM simulation) on the experimental specimen response. The test is usually a tensile test on a round-notched cylindrical bar. The present paper shows a novel inverse procedure aimed to estimate the material parameters of the Gurson-Tvergaard-Needleman (GTN) porosity-based plastic damage model by means of experimental data collected using image analysis. The use of digital image processing allows to substitute the load-displacement curve with other global quantities resulting from the measuring of specimen profile during loading. The advantage of this analysis is that more data are available for calibration thus allowing a greater level of confidence and accuracy in model parameter evaluation. © Springer Science+Business Media B.V. 2007.

Keywords: Damage mechanics | Image analysis | Inverse methods | Machine design | Parameter identification

Abstract: This paper deals with the calorimetric analysis of fatigue mechanisms of an aluminium alloy. Local 1D and 2D expressions of the heat diffusion equation were used to separately estimate the coupling and dissipative sources accompanying the fatigue test. The image processing was based on local approximations of surface temperature fields provided by an IR camera. The set of approximation functions accounted for the spectral properties of the sought sources. The analysis of thermoelastic source distribution allowed us to point out the possible heterogeneous character of fatigue loading from the beginning of the test. We observed that the zones where thermoelastic source amplitudes were the highest were potential loci of fatigue crack onset. On the other hand, such fine results on the dissipative source distribution were hard to obtain because of low signal-to-noise ratios. Nevertheless, we observed that the global dissipated energy rates increased linearly with the loading frequency. © 2006 Elsevier Ltd. All rights reserved.

Keywords: Aluminium alloy | Calorimetric analysis | Fatigue dissipation | Thermal images | Thermoelastic sources

Abstract: The present work presents the devising of a new highly automated artificial vision inspection (AVI) tool for real-time defect detection and classification on circular knitting machines. The tool is based on the combination of statistical analysis, Image Processing and an artificial neural network (ANN) approach. The tool (software + hardware) is directly attached to a circular knitting machine and the inspection is performed on-line during other common operations like laser cutting and ironing. The automatic inspection allows the real-time detection and classification of the most frequently occurring types of defects on knitted fabrics, which are significant for purposes of quality control and fabric grading. The reliability of the detection tool, i.e. the ratio between defect detected and effective defects is about 93%. The AVI system has been developed by the Department of Mechanical Engineering, University of Florence (Italy), and the textile research centre Tecnotessile s.r.l. of Prato (Italy).

Keywords: Image processing | Knitting machines | Neural network | Radon transform | Real time | Skewness

Abstract: This work provides an automatic and non-intrusive tool to objectively monitoring the raising process by measuring the height and the density of the fibres emerging from a raised cloth (pile). These parameters are assessed by a numerical procedure, which elaborates the images provided by an appositely developed machine-vision system. The proposed approach allows the investigation and the control of the raising process and has been validated by experimental measurements performed on a set of specimens (cloths) with several raising degrees. The comparison between the results obtained by the proposed procedure and the ones coming from a widely accepted textile-measuring device (fabric assurance by simple testing, FAST) is also provided. © 2005 Elsevier B.V. All rights reserved.

Keywords: Cloth raising | Image processing | Machine-vision design | Pile density | Pile height

Abstract: In this paper the results of an experimental investigation on the effect of subcritical damage on the residual strength properties of notched composite laminates are presented. A procedure based on the digital image correlation method was applied to laminates subjected to static and fatigue tensile loading. The digital image correlation method (DICM) is a whole-field technique that calculates surface displacements and strains from digital images characterized by a random distribution of intensity grey levels. Graphite/PEEK (polyether ether ketone) and graphite/epoxy laminates with different stacking sequences were analysed and the damage progression near the stress riser was evaluated by means of the strain maps obtained by digital image correlation. It was found that damage developing before final fracture may significantly affect the structural performance of composite laminates. The digital image correlation technique allowed clarification of the beneficial or detrimental role played by the different failure mechanisms on the strain redistribution around the hole and, as a consequence, on the residual strength and fatigue life of notched samples. The findings of the investigation suggest that the DICM is an efficient and reliable tool for full-field monitoring and detailed damage characterization of structural composite elements. © IMechE 2005.

Keywords: Composite materials | Damage | Digital image correlation | Fatigue | Notch

Abstract: Research was carried out by Tecnotessile Societa Nazionale di Ricerca Tecnologica r.l. in collaboration with the Department of Mechanics and Industrial Technology of the University of Florence to develop a methodology and software for measuring the pile depth and pile density of fabrics in real time. The research concentrated on napped wool and wool blend fabrics. The method is based on the use of artificial vision and was compared with results produced by FAST testing. The results of pile depth measurement are reported in the present article. The research comprised the following phases: HR image acquisition, HR image processing, processing of numerical information and definition of required values, low resolution image acquisition and processing, creation of Feed Forward Back Propagation neural network, and development of suitable software.

Abstract: Experimental, analytical and numerical methods of measuring the surface density of the pile of napped fabrics are presented. Surface density of pile is defined as the ratio between the weight of the pile extending above the fabric and the area of the sample to which it belongs. Samples were weighed, shaved and reweighed and the area of the sample was calculated from the number of pixels on a high-resolution image. The density of the fibre removed was estimated as the difference in density of the sample before and after shaving. A non-intrusive analytical method based on the height, diameter and number of pile fibres and a numerical method are described. Calculations based on pure wool and wool blend are presented and compared with the results obtained using the experimental method.

Abstract: This paper presents a 3D optical digitiser based on an active stereo vision aproach. The system is composed of a digital camera, a multimedia projector and software to control the hardware and process the images. The proposed solution integrates an active coded light method with a photogrammetric procedure in order to allow the acquisition of complex surfaces. In the work, experimental tests have been conducted with a nominal model and styling components of two-wheeler vehicles. The measurement process and the experimental results have been analysed to verify usability and accuracy of the methodology.

Keywords: Coded light | Photogrammetry | Reverse Engineering | Stereovision

Abstract: The planning of the hip prosthesis surgical operation is usually performed manually by the surgeon, who 'draws' on a patient's X-ray image the outline of the prosthetic stem in order to choose the one most suitable for the case at hand. In an attempt to give some repeatability and objectivity to the planning phase, a procedure has been devised for hip prosthesis' stem selection based on the extraction of the femoral relevant outlines. This work presents a computer aided method aimed at automatically extracting the medulla duct outlines from a human femur radiographic image. The outlines are retrieved by referring to a suitable geometric model of the generic femoral cross-section; the projection function obtained by simulating the radiographic acquisition of such a model is fitted on the grey-level functions corresponding to the rows of the actual digitised radiographic image by means of a least squares algorithm. The resulting outlines are used in a software tool performing the hip prosthesis pre-operational planning. © 2003 Published by Elsevier B.V.

Keywords: Medical images processing | Model-based image processing | Surgery aiding tools

Abstract: This paper is concerned with small strain measurement utilizing the numerical processing of digital images. The proposed method has its theoretical basis in digital signal analysis and, from a methodological point of view, it can be considered as an extension to digital images of the well-known white light speckle photography technique. That conventional method is based on the analysis of photographic plates that are exposed twice (before and after the specimen deformation) with the image of a random speckle pattern that has been previously printed on the test piece surface. The digital speckle correlation advantages consist of requiring a very simple specimen preparation and, mainly, of allowing the strain field computation just by numerical elaboration of the acquired images. In this paper, the theoretical basis of the technique and some valuable improvements to the known analogous methodologies are presented. Finally, test results for an application of digital speckle correlation are shown and advantages and disadvantages of the technique are elaborated. In addition, further developments in this area are discussed.

Keywords: Image processing | Speckle correlation | Speckle methods | Speckle photography | Strain analysis

Abstract: This work presents a procedure aimed at automatically extracting the medulla duct outlines from a human femur radiographic image. The outlines are retrieved by referring to a suitable geometric model of the generic femoral cross section; the projection function deriving from such a model is fitted on the grey level values corresponding to the rows of the digitised radiographic image by means of a least square algorithm. The resulting outlines are used in a software system performing the hip prosthesis pre-operational planning.

Abstract: The main aims of this paper are to describe the thermographic methodologies currently used in Italy for the rapid evaluation of the fatigue limit and to describe the local energy approach actually under development by the authors. Thermographic methodologies currently used in Italy for the rapid evaluation of the fatigue limit were applied to two stainless steels (AISI 304 atad AISI 409). All the experimental results here obtained are in good agreement with the respective values reported in literature. An experimental programme for the local energy approach is under development: its main characteristic consists in doing, besides the usual thermal measurements made by thermography, mechanical measurements in order to evaluate the mechanical energy locally dissipated inside the material. This experimental research is part of an interuniversity research programme and it is made on stainless steel (AISI 304) notched specimens. © 2002 SPIE · 0277-786X/02/$15.00.

Keywords: Fatigue limit evaluation | Local energy approach | Thermographic methodologies

Abstract: This work illustrates a computer program designed to aid surgeons in selecting the hip prosthesis femoral component during the preoperation planning stage of hip replacement surgery. Starting from the processing of the patient's coxo-femoral region X-ray image, the program, called Hippin, interacts with the user to outline the femoral region, including the head and the inner contour of the proximal femur. It automatically examines all possible couplings with the patient's femur outlines from a database containing the outlines of the available prostheses created by digitizing the templates normally used in preoperation planning. The resulting images enable the surgeon to visually compare all the alternatives. In addition, the program provides numerical values for the distances between the physiological rotation and prosthesis centers, helping the surgeon in selecting from among the possibilities. The program has been validated by comparing the computer results with actual surgeon selections. (C) 2000 Elsevier Science Ireland Ltd.

Keywords: Hip prosthesis | Image processing | Preoperation planning

Abstract: The phase stepping technique has recently been applied to the automated analysis of photoelastic fringes to determine the isoclinic parameter and the relative retardation. Generally, in these methods the error of quarter-wave plates, due to common manufacturing tolerances, influences the determination of the isoclinic parameter and the fringe order. In this paper a new phase stepping method in which the influence of quarter-wave plate error is null on the isoclinic parameter and negligible on the fringe order is proposed. The theoretical results have been confirmed by experimental tests.

Keywords: Image processing | Phase stepping | Photoelasticity

Abstract: The analysis of bone-remodelling processes by means of the relative radiographic follow-up has been proven to be a useful clinical diagnostic tool. A previous study has introduced a computerized, automatic, video-densitometric analysis. The main point of this procedure is that it potentially allows an objective, quantitative analysis of bone remodelling processes. This assertion is addressed by the present study. In particular, this study attempts to assess the repeatability of this procedure and to identify the main sources of noise.

Keywords: Bone-remodelling | Design of experiments | Diagnostics | Digital radiography | Factorial plane | Hip prosthesis | Image processing | Robustness | Video-densitometric analysis