黑龙江科技学院学报2013，Vol.23Issue(1)：83-88,6.DOI:10.3969/j.issn.1671-0118.2013.01.018
保留边界特征的点云简化算法
Research on point cloud simplification with boundary features reservation
摘要
Abstract
This paper proposes a simplification method for point cloud with boundary feature reservation for effective simplification of the point cloud. This algorithm consists of firstly using the 3D grid subdivision method to represent the spatial topology relationship of the scattered point cloud and calculate the κ-nearest neighbors for each data point, using the ball-fitting method to simply compute the curvature and the directional normal vector, and then identifying and reserving all the boundary points according to the ratio of the number of projected points, setting the desired thresholds by the specific situations, and classifying the non-boundary points through these thresholds, and finally simplifying the scattered point cloud according to comparative study of curvature and mean curvature of the points and the proportion of reserved points in their κ-nearest neighbors. The algorithm is verified by reducing some typical point cloud cases with various surface features. The experimental results indicate that the algorithm, marked by setting the threshold size according to simplification requirements, allows the direct and effective reduction of point cloud, while preserving detail feature of point cloud model, with a simplification proportion up to 25%-40%. This method can fulfill the requirements for simplifying different point cloud and improve the efficiency of computer operation.关键词
散乱点云/数据简化/法向量/曲率/边界特征提取Key words
scattered point cloud/data simplification/normal vector/curvature/boundary extraction分类
机械制造引用本文复制引用
赵伟玲,谢雪冬,程俊廷..保留边界特征的点云简化算法[J].黑龙江科技学院学报,2013,23(1):83-88,6.基金项目
国家自然科学基金项目(51075128) （51075128）
国家科技重大专项项目(2010ZX04016-012) （2010ZX04016-012）
博士后研究人员落户黑龙江科研启动资助金项目(LBH-Q12019) （LBH-Q12019）
