Segmentation of Scanned Mesh into Analytic Surfaces Based on Robust Curvature Estimation and Region Growing
Segmentation of Scanned Mesh into Analytic Surfaces Based on Robust Curvature Estimation and Region Growing
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DOI：
10.1007/11802914_52
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发表时间：
2006-07
期刊：
影响因子：
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通讯作者：
T. Mizoguchi;H. Date;S. Kanai;T. Kishinami
中科院分区：
文献类型：
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作者：
T. Mizoguchi;H. Date;S. Kanai;T. Kishinami
为了将激光或X射线CT扫描的网格模型有效地应用于设计、分析和检查等，优选地，将它们分割成期望的区域作为预处理。工程零件通常覆盖有分析曲面，例如平面、圆柱体、球体、圆锥体和圆环体。因此，必须从网格模型中提取零件边界的部分作为区域，其中每个部分都可以由一种类型的分析表面表示。在本文中，我们提出了一种新的网格分割方法，用于此目的。我们使用网格曲率估计与尖锐边缘识别，和非迭代区域生长提取区域。所提出的网格曲率估计对测量噪声具有鲁棒性。此外，我们提出的区域增长，使找到更准确的边界的基础表面，并分类提取的分析表面到更高级别的表面类：圆角表面，线性挤出表面和表面的革命比现有的方法。
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.