离散数据点集的3D三角划分算法研究  

Research on 3D Triangulation Algorithm for Scattered Data Points

作　　者：王宏志[1] 刘江[1] 张世荣[1] 

机构地区：[1]北京科技大学

出　　处：《工具技术》2008年第4期85-89,共5页Tool Engineering

摘　　要：在实物测量造型过程中,根据离散点集进行三角网格划分是其关键环节之一,也是进行后续进行曲面重构的前提和基础。本文在当前的三角网格划分方法比较之后,提出了一种散乱点集的三角网生长算法,该算法无须对离散点集所对应的自由曲面进行分片投影,直接在3D空间从已划分区域边界到未划分区域按照Delaunay准则生成三角网格,并给出了用此算法处理散乱数据的试验结果。In the process of physical measurement and modeling, setting scattered data points triangular mesh is not only one of the key links, but also is the precondition and foundation of the follow - up.surface reconstruction. After the analysis of different algorithms which deal with triangulation of scattered data points, a growth triangulation algorithm for scattered data points is put forward. This algorithm solves the problem that data points must be partitioned for multi - projection realized by traditional 2D triangulation methods. In the 3D triangulation process, the triangular mesh spreads from the boundary of triangulated field to untreated field according to the Delatmay criteria, and finally covers the whole surface. In this paper the experimental results using this growth triangulation algorithm are also given.

关 键 词：离散点集 三角网格 曲面重构 生长算法 Delaunay准则 

分 类 号：O241.5[理学—计算数学] TP391.41[理学—数学]