综合平均曲率与网格边的特征线提取方法

A FEATURE LINE EXTRACTION METHOD COMBINING MEAN CURVATURE WITH MESH EDGES

随着数字几何获取技术的发展,大量的复杂形体采用网格模型表示。而网格模型的特征线或特征边缘的识别和提取是后续开展几何和特征识别的基础工作,为此提出一种综合平均曲率与网格边的三角网格模型特征线提取方法。分两次提取:首先利用三角面片法矢夹角大小对模型中的尖锐边进行初次提取特征点;然后综合平均曲率与网格边的关系对特征点进行二次提取;最后用两次提取边的顶点作为特征点,进行分类分组处理拟合成特征线。经过实例验证,该算法可以快速地提取尖锐边和过渡边等,具有很好的提取效果。

With the development of digital geometry technology,a large number of complex shapes are represented by the mesh model. It is the basic work for follow-up geometry and feature recognition to identify and extract feature lines.Thus,a feature line extraction method combining mean curvature with mesh edges is presented. Firstly,the angle between the normal of adjacent triangles is used for the initial extraction of sharp edges. Then the feature edges are extracted according to the relationships between concave-convex properties and mean curvature of the surface. Finally the vertices of the extracted feature edges are classified and linked into feature lines. The case study verifies that the proposed algorithm can extract sharp edges and transition feature edges efficiently and effectively.