摘要
通过分析现有对测量数据精简算法的不足,提出了根据曲率精简点云的新方法,给出了散乱点的邻域搜索、曲率估算和精简原则。对具有不同特征的测量数据进行了精简测试分析,结果证明了该算法的有效性和实用性。
Through analyzing the shortcomings of existing measured data reduction methods, a new I point cloud reduction method based on curvature estimation is proposed, which gives the algorithms for neighborhood searching, curvature estimate and reduction. The availability and practicability of the proposed method are proved by testing and analyzing some measured data with different characteristics.
出处
《机械设计与制造》
北大核心
2006年第8期37-38,共2页
Machinery Design & Manufacture
基金
山东省自然科学基金项目(Y2004G10)
山东省教育厅科技攻关资助项目(03POZ)
关键词
反向工程
测量数据
曲率估算
数据精简
Reverse engineering
Measured data
Curvature estimation
Data reduction
