Principal Curvature-Driven Segmentation of Mesh Models: A Preliminary Assessment (original) (raw)
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Lecture Notes in Computer Science, 2006
For effective application of laser or X-ray CT scanned mesh models in design, analysis, and inspection etc, it is preferable that they are segmented into desirable regions as a pre-processing. Engineering parts are commonly covered with analytic surfaces, such as planes, cylinders, spheres, cones, and tori. Therefore, the portions of the part's boundary where each can be represented by a type of analytic surface have to be extracted as regions from the mesh model. In this paper, we propose a new mesh segmentation method for this purpose. We use the mesh curvature estimation with sharp edge recognition, and the non-iterative region growing to extract the regions. The proposed mesh curvature estimation is robust for measurement noise. Moreover, our proposed region growing enables to find more accurate boundaries of underlying surfaces, and to classify extracted analytic surfaces into higher-level classes of surfaces: fillet surface, linear extrusion surface and surface of revolution than those in the existing methods.
A Review on Mesh Segmentation Techniques
International Journal of Engineering, 2017
18 Abstract—Mesh segmentation plays a major role in modeling, shape compression, simplification, texture mapping, and skeleton extracting. The main goal of the mesh decomposition techniques is to segment the shape into parts in the preprocessing step. Each part acts as a dependent object which can identify the logic characteristics of the shape, in the preprocessing step. The techniques can be based on human perception (meaning components), geometric attributes or mesh components (vertices, edges, faces). This paper presents a comprehensive comparative study of the mesh segmentation techniques in terms of features and limitations. Finally, we figure out the most important challenges and recommendations for the mesh segmentation techniques.
Curvature estimation for segmentation of triangulated surfaces
Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062)
An important aspect of reverse engineering is the production of digital representations of physical objects for CAD systems. The first stage involves taking 3D coordinate measurements for points on the surface of the object and producing in general an unstructured set of points, called a point cloud. A triangulated surface can be generated from such a point cloud, allowing copies of the original object to be manufactured. However, these triangulated surfaces generally consist of a very large number of triangles with small errors in the positions of their vertices. In many cases the original object is made up of parts of a number of simple geometric objects. Our aim is to segment the triangulated surface into a small number of components, each of which approximates to part of a simple geometric shape. We have developed algorithms for curvature estimation in order to support a 'region growing' method of segmentation.
Mesh Segmentation - A Comparative Study
Shape Modeling International, 2006
Mesh segmentation has become an important compo- nent in many applications in computer graphics. In the last several years, many algorithms have been proposed in this growing area, offering a diversity of methods and vari- ous evaluation criteria. This paper provides a comparative study of some of the latest algorithms and results, along sev- eral axes. We evaluate only algorithms
Curvature Based Mesh Improvement
It is very important to improve the quality of surface meshes for numerical simulations, solid mesh generation, and computer graphics applications. Optimizing the form of the mesh elements it is necessary to preserve new nodes of the mesh as close as possible to a surface approximated by the initial mesh. This paper proposes a novel technique in which both of the requirements to mesh improvement are implemented. In the method presented here the new location of each node is found using values of principal curvatures in this node. Such procedure allows preserving new mesh very close to the initial surface while improving element quality. The method has been successfully tested on triangular meshes both for analytical surfaces (sphere, ellipsoid, paraboloid) and for arbitrary surfaces with great number of points. Comparison of the deviation of the mesh optimized by our method and by Laplacian smoothing from the original analytical surfaces shows advantage of the proposed method.
Surface mesh segmentation and smooth surface extraction through region growing
Computer Aided Geometric Design, 2005
Laser range-scanners are used in fields as diverse as product design, reverse engineering, and rapid prototyping to quickly acquire geometric surface data of parts and models. This data is often in the form of a dense, noisy surface mesh that must be simplified into piecewise-smooth surfaces. The method presented here facilitates this time-consuming task by automatically segmenting a dense mesh into regions closely approximated by single surfaces. The algorithm first estimates the noise and curvature of each vertex. Then it filters the curvatures and partitions the mesh into regions with fundamentally different shape characteristics. These regions are then contracted to create seed regions for region growing. For each seed region, the algorithm iterates between region growing and surface fitting to maximize the number of connected vertices approximated by a single underlying surface. The algorithm finishes by filling segment holes caused by outlier noise. We demonstrate the algorithm effectiveness on real data sets.
3D Mesh Segmentation Methodologies for CAD applications
Computer-Aided Design and Applications, 2007
3D mesh segmentation is a fundamental process for Digital Shape Reconstruction in a variety of applications including Reverse Engineering, Medical Imaging, etc. It is used to provide a high level representation of the raw 3D data which is required for CAD, CAM and CAE. In this paper, we present an exhaustive overview of 3D mesh segmentation methodologies examining their suitability for CAD models. In particular, a classification of the various methods is given based on their corresponding underlying fundamental methodology concept as well as on the distinct criteria and features used in the segmentation process.
Geometry and Topology-based Segmentation of 2-Manifold Triangular Meshes in R3
British Journal of Applied Science & Technology, 2017
This manuscript reports a geometrical and a topological methods to segment a closed triangular 2-manifold mesh M ⊂ R 3. The mesh M does not self-intersect) and has no border (i.e. watertight. Geometrical and topological segmentation methods require a Boundary Representation (BRep) from M. Building the BRep for M uniforms the triangle orientations, and makes explicit triangle and edge-counter edge adjacency. In the context of Reverse Engineering, the sub-meshes produced by the segmentation are subsequently used to fit parametric surfaces, which are in turn trimmed by the sub-mesh boundaries (forming FACEs). A Full Parametric Boundary Representation requires a seamless set of FACEs, to build watertight SHELLs. The fitting of parametric surfaces to the triangular sub-meshes (i.e. sub-mesh parameterization) requires quasi-developable sub-meshes.
Re-triangulation of existing surface meshes with high curvatures
This work describes an automatic algorithm for unstructured mesh regeneration on arbitrarily shaped threedimensional surfaces. The arbitrary surface may be: a triangulated mesh, a set of points, or an analytical surface (such as a collection of NURBS patches). To be generic, the algorithm requires the implementation of three abstract methods. The first, given a point location, returns the desired characteristic size of a triangular element at this position. The second method, given the current edge in the boundary contraction algorithm, locates the ideal apex point that forms a triangle with this edge. And the third method, given a point in space and a projection direction, returns the closest point on the geometrical supporting surface. This work also describes the implementation of these three methods to re-mesh an existing triangulated mesh that might present regions of high curvature. In order to test the efficiency of the proposed algorithm of surface mesh generation and implementation of the three abstract methods, results of performance and quality of generated triangular element examples are presented.
Mesh Segmentation Using the Platonic Solids
2011
Mesh segmentation has become an important step in model understanding and can be used as a useful tool for different applications, for instance, modeling, computer aided design (CAD), and reverse engineering. In this paper, we present a novel application of the platonic solids to find direction vectors for grouping the surface mesh elements. Normal vectors of the faces of the selected platonic solid are defined as the direction vectors. Our algorithm divides a polygonal mesh into the color regions (segments) with polygonal elements with normals that correspond to the direction vectors. Results of experiments on real 3D models demonstrate the performance and efficiency of the proposed algorithm. The original contribution in this paper is using normals of the faces of the platonic solids as the direction vectors for grouping mesh elements of the 3D surface meshes.