Abstract: In a digital world where technological development allows the implementation of computer-based methods that can objectively support human activities, it is no more conceivable that activities such as the analysis, classification, and reconstruction of archaeological ceramics are made manually. This determines that expert operators are involved in time-consuming, tedious, poorly repeatable, and reproducible activities whose results depend on his/her experience. This problem concerns the need for robust and reliable automatic methods supporting the operator in these activities. To address these problems, in the last years, the University of L'Aquila research group published robust and reliable methods based on the codification of archaeologists’ knowledge in recognizing the most significant geometric and morphological features of sherds. With such tools now available, producing more objective knowledge referring to a huge amount of sherds, the need arises to develop computer-based systems capable of sharing this knowledge. For this purpose, in this paper, a dedicated database is proposed. Particular efforts were made to implement an intuitive and interactive web interface with commands that co-determine the essential interaction of the archaeologist with the fragments in the traditional method.

Keywords: Automatic features recognition | Computer methods in archaeology | Innovative representation scheme | Semantic annotations | Web-based application

Abstract: The alignment of large datasets associated with 3D reconstructions is still an open issue in the scientific community. Among the several strategies available in the literature, some are based on using geometrical features. In this paper, the Authors have investigated the reliability of associating ideal planes with non-ideal roof features, which may be used to realign 3D terrestrial reconstructions. The obtained results underline a deep influence from noise, which affects the non-ideal roof feature and ideal plane association, and the necessity to define additional experiments to confirm the robustness of the solution.

Keywords: feature-based alignment | marker-less alignment | non-ideal feature approximation | terrestrial point-cloud

Abstract: The paper proposes a new recognition rule to automatically identify the spine line by detecting vertebral apophyses from discrete models of human backs collected by 3D scanning. Unlike previous 3D optical approaches, the process described here aims to directly detect spinal apophyses, following the posturologist’s method. These anatomical landmarks are identified not as areas of the back surface with specific shapes, but by searching for appropriate local shape perturbations. Except for vertebral prominences that are convex regions, spinal apophyses are generally unrelated to specific surface shapes. The rule has been tested on several human backs. For each, an experienced operator identified the spinal apophyses from palpation and indicated their position by applying an adhesive marker on the back surface. These positions are used as a reference to compare the vertebral apophyses automatically localized by the methodology proposed here. The experimental results show that the rule discriminates well even blurred vertebral prominences.

Keywords: 3D optical methods | Local shape analysis | Shape index | Spinal apophyses recognition | Spine line

Abstract: These authors presented an automatic computer-based method for morphological feature segmentation and recognition for thoracic and lumbar human vertebrae in a previous paper. The method analyses high-density discretized models by segmentation and recognition rules codifying the vertebra morphology information, which does not change between different subjects. The methodology has been demonstrated to be valid and repeatable in segmenting and recognizing morphological features of vertebrae. The proposed one gives repeatable and reproducible results concerning the traditional manual methods. Nonetheless, the method has been tested only on human lumbar and thoracic vertebrae without distinctive pathologies. This paper aims to extend this methodology for much wider use by analyzing single vertebrae affected by common defectiveness in archaeological and medical fields. The results of the experimentations, analyzed by a skilled anthropologist and radiologist, show that the method correctly segments the analyzed morphological features, also for thoracic and lumbar vertebrae with defectiveness: in particular, defects that alter the shape of features or the symmetry of the vertebra, determine the absence of a feature, or heavily change the spatial distribution of the anterior part respect to the posterior one, have been analyzed.

Keywords: 3D medical image analysis | Feature recognition | Thoracic and lumbar vertebrae analysis | Vertebrae analysis computer-based methods

Abstract: The study of potteries is still today almost entirely performed manually by archaeologists. The primary limits of the traditional approach are lack of repeatability in the results, the time required for the analysis and difficulty in exchanging information between researchers. Taking advantage of the previous research results obtained by the Authors in this field, a fully automated procedure for the analysis and cataloguing of potteries is presented in this paper. The procedure allows performing the geometric and semantic analysis of sherds, starting from their 3D scanned model. The method can also determine a set of meaningful measurements of the analyzed sherds and classify them according to the analysis results. Finally, the results are collected into a public and web-based application, which can be interacted with by interested people.

Keywords: 3D database | Computer-aided procedure | Pottery analysis | Semantic segmentation

Abstract: In the field of optical 3D scanning for healthcare applications, low-cost depth cameras can be efficiently used to capture geometry at video frame rates. However, the complete reconstruction of anatomical geometries remains challenging since different scans, collected from multiple viewpoints, must be aligned into a common reference frame. This paper proposes a fully automatic procedure to align scans of the upper limb patient’s anatomy. A 3D optical scanner, obtained by assembling three depth cameras, is used to collect upper limb acquisitions. A relevant dataset of key points on the hand and the forearm geometry is then determined and used to automatically obtain a rough 3D alignment of the different scans. Hand key points are identified through a neural network, which works on RGB images captured by the depth cameras; forearm key points are recognized by directly processing the point clouds through a specifically designed algorithm that evaluates the skeleton line of the forearm. The approach was tested on forearm acquisitions, and the results were compared to alternative alignment methodologies.

Keywords: 3D optical scanning | automatic point clouds alignment | depth cameras | upper limb anatomy

Abstract: Developing an automatic process for the segmentation and dimensional characterization of high-semantic level features from a ceramic find is an essential prerequisite for obtaining faster, reproducible, and more accurate measurements than the manual approach. These measurements are essential for analyzing, interpreting, and classifying the archaeological pottery, comparing and analyzing similarities, identifying the presence of standard attributes in the ceramics recovered from a specific archaeological site, or studying ancient manufacturing technologies. This paper proposes a new methodology for the recognition and dimensional measurement of a specific class of geometric features starting from high-density tessellated models acquired by 3D scanners, the Constant-Radius Sweeping Features (CRSFs). The recognition process is performed based on a fuzzy algorithm, which aggregates similar adjacent nodes, according to values of appropriate membership functions, into a single geometric feature. CRSFs are frequently seen in ancient artifacts as convex traces on the ceramic surface, such as plastic and molded reliefs, or concave features, such as engravings, graffiti, working signs, and impressions/stampings. Although they are frequently characterized, from a geometric point of view, by free-form surfaces, CRSFs may also be axially symmetrical geometry: this occurs quite often in archaeological pottery in correspondence with rims, bases, or external walls. In the proposed experimentation, the new methodology is applied to three fragments belonging to the same ceramic vessel and sharing a part of its rim. The results show that the algorithmic implementation of rules for CRSF recognition and measurement enables the automation of the entire process, from feature segmentation to the evaluation of the relevant characteristic dimensions, with the benefit of obtaining more robust and precise measurements than those performed manually. Furthermore, in some circumstances, the methodology proposed here allows for assessing dimensional attributes that would otherwise be impossible to evaluate by conventional methods: this is the case of CRSF not attributable to analytical geometric types, as frequently occurs in archaeological ceramics in the form of decorations, grooves, and processing marks.

Keywords: Computer methods in archaeology | Dimensional features for cultural heritage | Fuzzy logic | Geometric feature recognition

Abstract: igital representations of anatomical parts are crucial for various biomedical applications. This paper presents an automatic alignment procedure for creating accurate 3D models of upper limb anatomy using a low-cost handheld 3D scanner. The goal is to overcome the challenges associated with forearm 3D scanning, such as needing multiple views, stability requirements, and optical undercuts. While bulky and expensive multi-camera systems have been used in previous research, this study explores the feasibility of using multiple consumer RGB-D sensors for scanning human anatomies. The proposed scanner comprises three Intel® RealSenseTM D415 depth cameras assembled on a lightweight circular jig, enabling simultaneous acquisition from three viewpoints. To achieve automatic alignment, the paper introduces a procedure that extracts common key points between acquisitions deriving from different scanner poses. Relevant hand key points are detected using a neural network, which works on the RGB images captured by the depth cameras. A set of forearm key points is meanwhile identified by processing the acquired data through a specifically developed algorithm that seeks the forearm’s skeleton line. The alignment process involves automatic, rough 3D alignment and fine registration using an iterative-closest-point (ICP) algorithm expressly developed for this application. The proposed method was tested on forearm scans and compared the results obtained by a manual coarse alignment followed by an ICP algorithm for fine registration using commercial software. Deviations below 5 mm, with a mean value of 1.5 mm, were found. The obtained results are critically discussed and compared with the available implementations of published methods. The results demonstrate significant improvements to the state of the art and the potential of the proposed approach to accelerate the acquisition process and automatically register point clouds from different scanner poses without the intervention of skilled operators. This study contributes to developing effective upper limb rehabilitation frameworks and personalized biomedical applications by addressing these critical challenges.

Keywords: 3D optical scanning | automatic point cloud alignment | depth cameras | neural network | upper limb anatomy

Abstract: 3D reconstructed models are becoming more diffused daily, especially in the Cultural Heritage field. These geometric models are typically obtained from elaborating a 3D point cloud. A significant limit in using these methods is the realignment of different point clouds acquired from different acquisitions, particularly for those whose dimensions are millions of points. Although several methodologies have tried to propose a solution for this necessity, none of these seems to solve definitively the problems related to the realignment of large point clouds. This paper presents a new and innovative procedure for the fine registration of large point clouds. The method performs an alignment by using planar approximations of roof features, taking the roof’s extension into account. It looks particularly suitable for the alignment of large point clouds acquired in urban and archaeological environments. The proposed methodology is compared in terms of accuracy and time with a standard photogrammetric reconstruction based on Ground Control Points (GCPs) and other ones, aligned by the Iterative Closest Point method (ICP) and markers. The results evidence the excellent performance of the methodology, which could represent an alternative for aligning extensive photogrammetric reconstructions without the use of GCPs.

Keywords: multi-UAV scanning registration | particle swarm optimization | point cloud registration | shape features recognition

Abstract: Ceramics analysis, classification, and reconstruction are essential to know an archaeological site's history, economy, and art. Traditional methods used by the archaeologists for their investigation are time-consuming and are neither reproducible nor repeatable. The results depend on the operator's subjectivity, specialization, personal skills, and professional experience. Consequently, only a few indicative samples with characteristic components are studied with wide uncertainties. Several automatic methods for analysing sherds have been published in the last years to overcome these limitations. To help all the involved researchers, this paper aims to provide a complete and critical analysis of the state-of-the-art until the end of 2021 of the most important published methods on pottery analysis, classification, and reconstruction from a 3D discrete manifold model. To this end, papers in English indexed by the Scopus database are selected by using the following keywords: “computer methods in archaeology”, “3D archaeology”, “3D reconstruction”, “3D puzzling”, “automatic feature recognition and reconstruction”. Additional references complete the list found through the reading of selected papers. The 125 selected papers, referring to only archaeological potteries, are divided into six groups: 3D digitalization, virtual prototyping, Fragment features processing, geometric model processing of whole-shape pottery, 3D Vessel reconstruction from its fragments, classification, and 3D information systems for archaeological pottery visualization and documentation. In the present review, the techniques considered for these issues are critically analysed to highlight their pros and cons and provide recommendations for future research.

Keywords: Automatic features recognition | Computer methods in archaeology | Computer-based methods for sherds classification and reconstruction | Mesh segmentation | Pottery profile detection | Pottery profile dimensions

Abstract: The traditional manual method of analysis of ceramic finds involves expert operators in long and routine activities whose results depend on their subjectivity, specialization, and professional experience. This implies that the analysis of sherds is carried out using few data affected by high uncertainty. These limitations are even more clear with fragments with small axially symmetric portions whose elements of the investigation are not axially symmetric, such as handles, spouts, decorations. In this way both the axis of symmetry of the original object and the reference planes and/or axes of the characteristic dimensions of the elements are identified with such approximations as to compromise subsequent analyses and comparisons. To overcome these limitations, in this paper a new computer-based procedure is proposed. As a case study, the analysis fragments of jugs/bowls with trilobed spouts found in the site of Amiternum, coming from 12th-13th century contexts are considered; their analysis is fundamental to analyze the site where they were found since there is no archival documentation about their use.

Abstract: The knowledge of the history, economy, and art of an archeological site is based on information that can be taken from ceramics analysis, classification, and reconstruction. The traditional methods used by the archeologists for their investigation are time-consuming, not reproducible, and repeatable, and the results depend on the subjectivity, specialization, personal skills, and professional experience of the operator. An as consequence, only a few indicative samples that have characteristic components are analyzed with wide uncertainties. In order to overcome these limitations, in the last years, some automatic methods for studying archeological pottery’s findings are proposed in the literature. To help all the researchers involved in this field, this paper aims to provide a complete and critical analysis of the state-of-the-art until the end of 2020 of the published methods on pottery classification and reconstruction from a 3D discrete manifold model. For this purpose, papers in English by the Scopus database are collected by using the following keywords: “computer methods in archaeology”, “3D archaeology”, “3D reconstruction”, “automatic feature recognition and reconstruction”, “3D puzzling”. The list is completed by additional references found through the reading of selected papers. The 35 selected papers are divided into three groups: Geometric model fragment processing, 3D information systems for archaeological pottery visualization and documentation, 3D puzzling of archaeological fragments. The results of the present review are focused on the presentation of the pros and cons of the techniques used on these different issues.

Keywords: 3D archaeology | Automatic feature recognition | Computer methods in archaeology | Computer-based methods for sherd classification and reconstruction | Surface segmentation

Abstract: UAV Photogrammetry is a quite widely use technology for 3D reconstruction of territory, thanks to its satisfying results in many fields of applications and its low cost. Most of researches that addressed this topic use Ground Control Points (GCPs) for scaling and georeferencing the acquired point-cloud. In this paper, due to the particular morphology of the surveyed territory that makes very difficult to define GCPs in the region of interest, an innovative technique based on geometrical features was used for orienting, scaling and georeferencing the 3D point-cloud. The case is the ancient Roman outlet of the Fucino emissary, sited in a very steep and not accessible area, near Capistrello (AQ) city, Italy. The obtained results show that the proposed methodology, although less accurate than standard one using GCPs, provides quite good results, so that it can be used where the use of GCPs is difficult or impossible.

Keywords: Archaeology | Feature-based alignment | UAV photogrammetry

Abstract: Purpose: This paper aims to enhance the visual quality of artificial above-ground structures, like pylons, masts, and towers of infrastructures and facilities, through a systematic design method for their morphological and structural optimization. Design/methodology/approach: The method achieves the functional and aesthetic goals based on the application of computer-aided tools. In particular, this is achieved according to three key steps: • Morphological development of landscape-related symbolism, environment, or culture and social needs. • Topology optimization of the design concept to reduce the structural weight and its visual impact. • Engineering of the resulting optimized structure. Practical implications: As a case study, the method is used for designing electricity pylons for the coastal territory of a Mediterranean European country, such as Italy. Citizens were involved during the identification phase of a symbolic shape for the concept development and during the final assessment phase. Research limitations/implications: The engineering phase has been performed by assembling standard lattice components with welded connections. Even if the use of this truss-like structure should lead to a minimum cost, the developed structure employs an additional 15%–20% of trusses and sheet metal covers the final cost is higher than a standard lattice pylon. Findings: The result is a structure with enhanced visual quality according to the international guidelines and fully complying with mandatory and functional requirements, such as regulatory and industrial feasibility, as well as those arising from social components. Originality/value: The method shows its potential in defining a custom design for lightweight structures with enhanced visual quality regarding the critical situation discussed here. The method considers both the subjective perception of citizens and their priorities and the landscape where the structures will be installed.

Keywords: computer-aided tool | design method | landscape impact | pylon | topology optimization | visual impact

Abstract: Background and objective: Because of the three-dimensional distribution of morphological features of human vertebrae and the whole spine, in recent years, to make more precise diagnoses and to design optimized surgical procedures, new protocols have been proposed based on analysing their three-dimensional (3D) models. In the related literature, processes of segmentation and morphological features recognition are essentially performed by a skilled operator that selects the interesting areas. So, being affected by the preparation and experience of the operator, this produces an evaluation that is poorly reproducible and repeatable for the uncertainties of a typical manual measurement process. Methods: To overcome this limitation, in this paper a new automatic method is proposed for feature segmentation and recognition of human vertebrae. The proposed computer-based method, starting from 3D high density discretized models of thoracic and lumbar vertebrae, automatically performs both the semantic and geometric segmentation of their morphological features. The segmentation and recognition rules codify some important definitions used in the traditional manual method, considering all the vertebra morphology information that is invariant inter-subject. Results: The automatic method proposed here is verified by analysing many real vertebrae, both acquired using a 3D scanner and coming from Computerized Tomography (CT) scans. The obtained results are critically discussed and compared with the traditional manual methods for vertebra analysis. The method has proven to be robust and reliable in the segmentation and recognition of morphological features of vertebrae. Furthermore, the proposed automatic method avoids the blurring of quantitative parameters get from vertebrae, resulting from poor repeatability and reproducibility of manual methods used in the state-of-the-art. Conclusions: Starting from the automatic segmentation and recognition here proposed, it is possible to automatically calculate the parameters of thoracic or lumbar vertebrae used in archaeology, medicine, or biomechanics or define their new ones.

Keywords: 3D medical image analysis | Computer methods for vertebra analysis | Shape segmentation | Thoracic and lumbar vertebrae | Three-dimensional measurement

Abstract: The detection of the symmetry axis from discrete axially symmetric surfaces is an interesting topic, which is transversal to various fields: from geometric inspection to reverse engineering, archeology, etc. In the literature, several approaches have been proposed for estimating the axis from high-density triangular models of surfaces acquired by three-dimensional (3D) scanning. The axis evaluation from discrete models is, in fact, a very complex task to accomplish, due to several factors that inevitably influence the quality of the estimation and the accuracy of the measurements and evaluations depending on it. The underlying principle of each one of these approaches takes advantage of a specific property of axially symmetric surfaces. No investigations, however, have been carried out so far in order to support in the selection of the most suitable algorithms for applications aimed at automatic geometric inspection. In this regard, ISO standards currently do not provide indications on how to perform the axis detection in the case of generic axially symmetric surfaces, limiting themselves to addressing the issue only in the case of cylindrical or conical surfaces. This paper first provides an overview of the approaches that can be used for geometric inspection purposes; then, it applies them to various case studies involving one or more generic axially symmetric surfaces, functionally important and for which the axis must be detected since necessary for geometric inspection. The aim is to compare, therefore, the performances of the various methodologies by trying to highlight the circumstances in which these ones may fail. Since this investigation requires a reference (i.e. the knowledge of the true axis), the methodologies have been applied to discrete models suitably extracted from CAD surfaces.

Keywords: axially symmetric surfaces | Axis of symmetry | geometric inspection | geometrical dimensioning and tolerancing | high-density triangular models

Abstract: From archaeological excavations, huge quantities of material are recovered, usually in the form of fragments. Their correct interpretation and classification are laborious and time-consuming and requires measurement, analysis and comparison of several items. Basing these activities on quantitative methods that process 3D digital data from experimental measurements allows optimizing the entire restoration process, making it faster, more accurate and cheaper. The 3D point clouds, captured by the scanning process, are raw data that must be properly processed to be used in automatic systems for the analysis of archeological finds. This paper focuses on the integration of a shape feature recognizer, able to support the semantic decomposition of the ancient artifact into archaeological features, with a structured database, able to query the large amount of information extracted. Through the automatic measurement of the dimensional attributes of the various features, it is possible to facilitate the comparative analyses between archaeological artifacts and the inferences of the archaeologist and to reduce the routine work. Here, a dedicated database has been proposed, able to store the information extracted from huge quantities of archaeological material using a specific shape feature recognizer. This information is useful for making comparisons but also to improve the archaeological knowledge. The database has been implemented and used for the identification of pottery fragments and the reconstruction of archaeological vessels. Reconstruction, in particular, often requires the solution of complex problems, especially when it involves types of potsherds that cannot be treated with traditional methods.

Keywords: 3D archaeology | Computer methods in archaeology | Information search and retrieval | Measurement precision in archaeol-ogy | Similarity metric

Abstract: The problem of matching fragments of three-dimensional (3D) objects has gained increasing attention, and several approaches have been developed to solve this problem. To date, however, to the best knowledge of the authors, there is no computer-based method supporting archaeologists in this activity. For this purpose, in this paper, a semi-automatic approach is proposed for the reconstruction of archaeological pottery fragments based on two-dimensional (2D) images. Firstly, the method, considering the curves as features, involves the extraction of edge curves by applying the Canny filter algorithm to the fragments’ image. Next, the wavelet transformation method is used to fit the edge curves and obtain the approximation coefficients. Then, the correlation coefficients between fragments are computed and the matching of fragments is done by comparing their values. The proposed approach is tested on some real cases. The results of the experimentation show, if compared with the state-of-the-art, that the method seems to be efficient and accurate in the reconstruction of pottery from 2D images of their fragments.

Keywords: Edge detection | Pottery fragment | Reconstruction | Wavelet transformation

Abstract: Additive manufacturing is a technology for quickly fabricating physical models, functional prototypes, and small batches of parts by stacking two-dimensional layered features directly from computer-aided design data. One of the most important challenges in this sector relates to the capability to predict the build time in advance, since this is crucial to evaluating the production costs. In this paper, an accurate method for obtaining build-time is proposed. This method is based on an advanced GCode analyzer written in Python following an object-oriented paradigm for scalability and maintainability. Various examples are used to demonstrate the reliability of the algorithm, while its potential applications are also illustrated.

Keywords: Additive manufacturing | Build time estimation | Manufacturing costs | Process planning

Abstract: Ceramic sherds are the most common finds in archaeology. They are complex to analyze and onerous to process. A large number of indistinct sherds coming from excavations must be preliminarily grouped in some categories. This clusterization helps the next phase, in which archaeologists classify the ceramics. Due to the difficulty of these preliminary, repetitive, and routine phases, a great deal of archaeological material remains unstudied in museum repositories or archaeological sites. An effective method to automate these routine phases is presented in this article. The proposed method performs a shape feature segmentation of the sherds, which is fundamental to undertake any further analysis, such as potsherds classification, reconstruction, or cataloging. A set of specific shape features, useful to understand the find properties, is defined and methods for recognizing them are proposed. The method's performance is tested in the analysis of some real, critical cases.

Keywords: 3D archaeology | Automatic feature recognition | computer methods in archaeology | surface segmentation

Abstract: By additive manufacturing technologies, an object is produced deposing material layer by layer. The piece grows along the build direction, which is one of the main manufacturing parameters of Additive Manufacturing (AM) technologies to be set-up. This process parameter affects the cost, quality, and other important properties of the manufactured object. In this paper, the Objective Functions (OFs), presented in the literature for the search of the optimal build direction, are considered and reviewed. The following OFs are discussed: part quality, surface quality, support structure, build time, manufacturing cost, and mechanical properties. All of them are distinguished factors that are affected by build direction. In the first part of the paper, a collection of the most significant published methods for the estimation of the factors that most influence the build direction is presented. In the second part, a summary of the optimization techniques adopted from the reviewed papers is presented. Finally, the advantages and disadvantages are briefly discussed and some possible new fields of exploration are proposed.

Keywords: Build orientation factors | Cost analysis | Multi objective optimization | Part build orientation

Abstract: Additive manufacturing (AM) is a group of processes which manufacture a part by adding sequential layers of material on each other. In the last decade, these processes have been extensively applied in industry for constructing small volumes of complex, customized parts. Since parts are built layer-by-layer, the build orientation affects the surface quality and the total cost of the part. The search for optimal build orientation is not trivial since these factors are, typically, in conflict with each other. The major limitation of the methods described in the literature to choose the optimal build direction is in the insufficient accuracy of the estimates of the manufacturing cost and of the surface quality. These factors are very complex to be estimated, and accuracy in their evaluation requires methods that are very time-consuming. On the contrary, in practical use, a multi-objective optimization process requires an objective function that is reliable and easy to be evaluated. In order to overcome these problems, in this paper, original methods to estimate the manufacturing cost and surface quality as a function of build orientation are presented. They are implemented, for the fused deposition modeling (FDM) technology, in a multi-objective optimization problem that is solved by an S-metric selection evolutionary multi-objective algorithm (SMS-EMOA), obtaining an approximation of the Pareto front. The final selection of the recommended orientation is performed by the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. Properly designed case studies are used to evaluate the reliability of the proposed method, and the results are compared with the state-of-the-art method to find optimal build orientation.

Keywords: Additive manufacturing | Build orientation | Multi-objective optimization | Surface quality

Abstract: The registration permits to positioning in a single reference system point clouds acquired from different points of view. Since this is typically obtained with an iterative numerical method, it represents an important source of error in the entire reverse engineering process. As all iterative methods, such errors depend on the choice of the initial solution; therefore, this process requires an expert user who, by using dedicated software, choices the sequence of clouds to be registered, imposes for each pairwise the first attempt registration, launches the iterative method, and verifies the final result. With the aim to minimize the error and the user's interaction, some devices are proposed in the market (turntable or the anthropomorphic arm, etc.). The above-mentioned hardware and software tools cannot be used in the cultural heritage applications involving large and detailed objects. In this paper, an automatic alignment method of point clouds is proposed. The method uses as inputs the constant radius features, which are frequently detectable on cultural heritage objects. The automatic alignment of the point clouds is based on the recognition, the segmentation, and the registration of the sweep lines identifiable from these features.

Abstract: Additive Manufacturing is a very time consuming technology. An estimation of the build time is fundamental to: Evaluate the production cost in budgeting process.Make use of optimization methods, which use as parameter the build time, for determining optimal build direction. In both these cases a fast and valid build time estimator, which can work with a few input data deducible from geometric model, is required. In the proposed paper a reliable parametric-based method to determine the build time for additive manufactured objects is provided. The implemented method is based on a back-propagation artificial neural network, which gives the possibility to implement the complex functions that elapse some driving build-time factors and the build time. The neural network training is based on data provided by a properly developed analyzer of the list of commands given to AM machines, which performs an analytical estimation of the build time. The implementation of the proposed methodology is illustrated and some comparisons between the real and estimated build-time are provided, then the results are critically analyzed.

Keywords: Adaptive model | Additive Manufacturing | Build time estimation | Process planning

Abstract: The paper aims at providing an overview on the current automation level of geometric verification process with reference to some aspects that can be considered crucial to achieve a greater efficiency, accuracy and repeatability of the inspection process. Although we are still far from making this process completely automatic, several researches were made in recent years to support and speed up the geometric error evaluation and to make it less human-intensive. The paper, in particular, surveys: (1) models of specification developed for an integrated approach to tolerancing; (2) state of the art of Computer-Aided Inspection Planning (CAIP); (3) research efforts recently made for limiting or eliminating the human contribution during the data processing aimed at geometric error evaluation. Possible future perspectives of the research on the automation of geometric verification process are finally described.

Keywords: Automatic geometric verification | Computer-Aided Inspection Planning | Error evaluation | Feature Recognition | GPS standards | Model of specification for tolerancing | Partition

Abstract: The construction of the artificial emissary of Fucino Lake is one of the most ambitious engineering buildings of antiquity. It was the longest tunnel ever made until the 19th century and, due to the depth of the adduction inlet, it required a monumental and complex incile, which, for functionality, cannot be compared to other ancient emissaries. The Roman emissary and its "incile" (Latin name of the inlet structure) were almost completely destroyed in the 19th century, when Fucino Lake was finally dried. Today, only few auxiliary structures such as wells, tunnels, and winzes remain of this ancient work. As evidence of the ancient incile remains a description made by those who also destroyed it and some drawings made by travelers who, on various occasions, visited the site. This paper presents a virtual reconstruction of the Roman incile, obtained both through the philological study of the known documentation, interpreting iconographic sources that represent the last evidence of this structure, and through the survey on the territory. The main purpose is to understand its technical functionalities, the original structures, and its evolution during the time, taking into account the evolution of the Fucino Lake water levels, technological issues, and finally o_ering its visual reconstruction.

Keywords: 3D virtual reconstruction This research received no external funding | Archaeology | Monumental heritage | Remote sensing

Abstract: Additive Manufacturing (AM) is a technology for quickly fabricating physical models, functional prototypes and small batches of parts, by stacking two-dimensional layered features, directly from computer-aided design (CAD) data. One of the most important challenges in this sector is represented by the capacity to predict in advance build time required for manufacturing a part because it's crucial to evaluate production cost. In this paper, an accurate method for obtaining build time is proposed. This method is based on an advanced GCode reader written in Python following an Object Oriented paradigm for scalability and maintainability. Some examples were used to demonstrate the reliability of the algorithm and possible uses of it are illustrated.

Abstract: The classification of ceramic archaeological fragments is based on shape, dimensions, decorations, technological elements, color and material. Nowadays, all of these features are still recognized and analyzed by a skilled operator. It follows that the resulting characterization of shape and sizes of archaeological fragments is poorly reproducible and repeatable. With a view to overcome these limitations, a computer-based methodology, able to extract automatically several quantitative information from high-density discrete geometric models acquired by the laser scanning of archaeological fragments, was proposed. In this paper, the set of quantitative information obtainable is furtherly broadened, by including the segmentation of some types of morphological features, the identification of the fragment shape type, the evaluation of the longitudinal profile and the estimation of a larger set of dimensional features. Finally, a new 3D information framework is proposed to store the large variety of quantitative information extracted.