摘要
提出一种散乱点云自适应切片算法,该算法建立点云动态空间索引结构,基于该结构快速准确获取切片邻域数据并确定各层切片位置,依据邻域数据与切片的位置关系将其分为正负两个区域,通过正负区域配对点连线与切片求交获取切片数据点,并采用最小生成树算法排序,得到有序的切片数据点,实现散乱点云的自适应切片,实例证明该算法适用于逆向工程中各种复杂型面点云数据,切片数据获取精度高,算法运行速度快。
An self-adaptive slicing algorithm for scattered points is proposed, which has four steps： first, the slicing neighbor points are obtained based on the spacial index structure of scattered points; second, the slicing neighbor points are divided into two parts; third, the slicing points are obtained by the intersecting between matching points of slicing neighbor data and the slice; fourth, the intersecting points are sorted with algorithm of Minimum Spannimg Tree. This algerithm can obtain slicing points accurately, effectively and has strongly adaptability of data type.
出处
《四川大学学报（工程科学版）》
EI
CAS
CSCD
北大核心
2010年第1期216-219,共4页
Journal of Sichuan University (Engineering Science Edition)
基金
国家高技术研究发展863计划资助项目(2006AA04Z105)
关键词
逆向工程
散乱点云
动态空间索引结构
最小生成树
自适应切片
reverse engineering
scattered points
spacial index structure
minimum spannirng
tree
self-adaptiveslicing
