摘要
提出了一种算法用于从散乱点云中重构曲线,点云通过一个滤波器后被细化.当点云足够细时,可以非常容易地给它定序,从而可以对点云进行曲线拟合或逼近;对于厚度变化不均匀的点云,将半径固定的选点窗口进行改进,引入一个自适应算法,能随点云厚度的变化调整窗口半径,改善滤波器性能.数值实验表明,算法简单、快速、有效,尤其当点云密度很大且厚度不均匀时,曲线重构的效果更好.
An algorithm for curve reconstruction from unorganized points is presented. By passing a (well-designed) filter, a point cloud is thinned and smoothed. When the point cloud is thin enough, it is not (difficult) to order the points and get an approximate curve. For point clouds with unevenly varying thickness, (fixedsized) window for point collecting cannot be applied to the whole point set. An adaptive method is (introduced) to adjust the window size. Numerical examples show that the algorithm is simple, fast and efficient, especially when the point cloud becomes very dense and noisy.
出处
《天津大学学报（自然科学与工程技术版）》
EI
CAS
CSCD
北大核心
2005年第7期654-658,共5页
Journal of Tianjin University：Science and Technology
基金
南开大学天津大学刘徽应用数学研究中心资助项目.
关键词
曲线重构
滤波
平滑
逆向工程
散乱点
curve reconstruction
filtering
smoothing
reverse engineering
unorganized points
