1,721,033 research outputs found
Performance evaluation and experimental characterization of a new automatic method for measuring vertebrae
No full textIn this paper performance evaluation and experimental characterization of a new automatic method for measuring vertebrae are analysed. Starting to a discrete valid geometric model of the vertebra, obtained from CT-scans or 3D scanning, the method measures algorithmically vertebrae. The proposed study is performed by analysing the most used dimensional features of lumbar and thoracic real vertebrae in anthropological investigations. The results are compared with the state-of-the-art methods for vertebra measurement
Automatic Segmentation of Constant Radius Secondary Features from Real Objects
No full textSecondary features, such as fillets, rounds, chamfers and grooves, are simple transitions between primary features, generally introduced in order to remove the sharp edges created by the intersection of primary features. Being able to distinguish secondary from primary features is important in various application contexts, such as reverse engineering, automatic geometric inspection of real scanned objects, and for preparation of models for FEM analysis and CNC tool-path generation. The process for the recognition of secondary features from high-density tessellated models of real work-pieces is intrinsically complex for several reasons. This explains why, currently, there are no methodologies able to recognize automatically secondary features and the investigation on secondary features is mostly focused on B-Rep models. In a previous paper, the authors proposed a method for secondary features recognition from discrete geometric models synthetically generated. Here the methodology is extended to discrete geometric models experimentally acquired, for which the recognition is a very complex process, due to the object discretization, to its non-ideal geometry and to measurement errors
An automatic method for feature segmentation of human thoracic and lumbar vertebrae
No full textBackground 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
Fillets, rounds, grooves and sharp edges segmentation from 3D scanned surfaces
No full textFillets, rounds, chamfers and grooves are secondary features which are typically present in real manufactured mechanical components to satisfy some manufacturing and functional requirements. Despite the broad array of research conducted on feature recognition, the investigation of secondary features is a relatively new topic. All of the pertinent studies have been focusedonly on the recognition of secondary features from B-Rep models. The recognition and segmentation of secondary features from a discrete model is a non-trivial problem due to the same geometric descriptors that may be applied to both primary and secondary features. Moreover, although in real-world mechanical parts primary features are planes, cylinders or cones, the secondary features may be non-analytical and complex-shaped geometries. Further sources of uncertainty are the measurement errors and non-ideal geometries of the real objects to which the method is applied. To overcome these problems, a new and original method to segment secondary features of tessellated geometric models is proposed. The method is based on the analysis of geometric-differential properties and provides specific strategies that reduce its sensitivity to all of the above-mentioned uncertainties without affecting its selectivity. The proposed method, described in detail in this paper, is tested in some very critical cases, and the results are presented and discussed
Automatic shape feature recognition for ceramic finds
No full textCeramic 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
Automatic analysis of pottery sherds based on structure from motion scanning: The case of the Phoenician carinated-shoulder amphorae from Tell el-Burak (Lebanon)
No full textOver the last few years, significant interest has been addressed in developing computer-based methods to document and analyze fragments of ceramics sherds in archaeology. This is because traditional manual processes do not allow for an objective, repeatable, and reproducible analysis of the large quantities of material needed to fully understand and explain human practices in various cultural contexts, such as the economy, daily life, and the material expression of religious beliefs. In that context, this paper proposes a fully digital methodology resulting from the constitution of an international research group coming from different scientific backgrounds: archaeologists with specific skills and experience in fast 3D geometry acquisition methods and researchers who developed and published the only available computer-based process for recognizing the geometric and morphological sherds features analyzed by archaeologists. The proposed methodology consists of two main parts: 1. 3D acquisition of sherds with the construction of the discrete 3D manifold model based on the Structure for Motion technologies; 2. recognition, segmentation, and dimensional characterization of morphological and geometrical features based on the codification and algorithmic implementation of the knowledge used by the archeologists in the traditional method. The method was applied to analyze a set of 133 sherds excavated at Tell el-Burak (Lebanon) to obtain, through the analysis of the namely Phoenician carinated-shoulder amphorae, new insights into the economic organization of the Phoenician homeland. The method demonstrated the potential for objectively, repeatedly, and reproducibly analyzing large quantities of sherds. Furthermore, it allowed studying sherds by generating new high-level knowledge from those acquired from 3D models; in particular, this paper introduces new morphological features that help the archaeologist classify fragments from an analysis of the rim's shape
An advanced GCode analyser for predicting the build time for additive manufacturing components
Full text linkAdditive 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
The integration of morphological design and topology optimization to enhance the visual quality of electricity pylons
Full text linkPurpose: 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
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