Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Segmentation through Variable-Order Surface Fitting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Methods to recover constant radius rolling ball blends in reverse engineering
Computer Aided Geometric Design
Robust Segmentation of Primitives from Range Data in the Presence of Geometric Degeneracy
IEEE Transactions on Pattern Analysis and Machine Intelligence
Range-Image segmentation and model reconstruction based on a fit-and-merge strategy
Proceedings of the seventh ACM symposium on Solid modeling and applications
Constrained fitting in reverse engineering
Computer Aided Geometric Design
Partitioning 3D Surface Meshes Using Watershed Segmentation
IEEE Transactions on Visualization and Computer Graphics
Shape segmentation using local slippage analysis
Proceedings of the 2004 Eurographics/ACM SIGGRAPH symposium on Geometry processing
Mesh Segmentation - A Comparative Study
SMI '06 Proceedings of the IEEE International Conference on Shape Modeling and Applications 2006
Surface mesh segmentation and smooth surface extraction through region growing
Computer Aided Geometric Design
Curvature estimation scheme for triangle meshes using biquadratic Bézier patches
Computer-Aided Design
Markov random fields for improving 3D mesh analysis and segmentation
EG 3DOR'08 Proceedings of the 1st Eurographics conference on 3D Object Retrieval
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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.