一种密集管道点云数据自动分割算法  

An Automatic Segmentation Algorithm for Dense Pipeline Point Cloud Data

作　　者：黄凯 程效军 贾东峰[3] 胡旦华 胡敏捷 Huang Kai;Cheng Xiaojun;Jia Dongfeng;Hu Danhua;Hu Minjie(College of Surveying and Geo-Information,Tongji University,Shanghai 200092,China;Key Laboratory of Advanced Engineering Surveying of National Administration of Surveying,Mapping and Geoinformation,Tongji University,Shanghai 200092,China;Department of Structural Engineering,College of Civil Engineering,Tongji University,Shanghai 200092,China;Fujian Electric Power Survey ＆ Design Institute Co.,Ltd.Power China,Fuzhou,Fujian 350003,China;Shanghai Merchant Ship Design and Research Institute,Shanghai 201203,China)

机构地区：[1]同济大学测绘与地理信息学院,上海200092 [2]同济大学现代工程测量国家测绘地理信息局重点实验室,上海200092 [3]同济大学土木工程学院建筑工程系,上海200092 [4]中国电建集团福建省电力勘测设计院有限公司,福建福州350003 [5]上海船舶研究设计院,上海201203

出　　处：《中国激光》2018年第11期158-166,共9页Chinese Journal of Lasers

基　　金：上海船舶研究设计院科技项目(JSJC2013206C204);广州市科技计划项目(201704030102)

摘　　要：提出了一种针对密集圆形管道点云数据的自动分割算法,通过八叉树结构将点云划分为若干个子块,并建立其空间邻域关系,采用基于法向量条件约束的随机采样一致性算法移除子块内的大区域平面,同时运用欧氏距离聚类和基于平滑条件约束的区域增长分割算法再次细化数据。实验结果表明:提出的自动分割算法在处理大小为6 m×12 m×16 m的点云空间数据时,4线程并行计算仅耗时9 s,精确率达到90%以上。因此,所提算法能够快速、准确地分割管道点云数据,具有较高的应用价值。An algorithm for the automatic segmentation of dense circular pipeline point cloud data is proposed. The cloud data is divided into several sub-blocks based on the octree structure, among which the spatial neighborhood relationship is established. The random sampling consensus algorithm based on the normal vector constraints is used to remove the large area plane within each sub-block and simultaneously, the Euclidean distance clustering and the region growing segmentation algorithm based on the smoothness constraints are used to refine the data again. The experimental results show that a 4 thread parallel computation only takes 9 s and the precision is larger than 90% when the proposed automatic segmentation algorithm is used to process the data with a size of 6 m×12 m×16 m in the point cloud space. Thus the proposed algorithm can be used for the quick and accurate segmentation of pipeline point cloud data and has a high application value.

关 键 词：测量 三维激光扫描 自动分割 随机采样一致性算法 密集管道 

分 类 号：P232[天文地球—摄影测量与遥感]