%0 Journal Article
%T Research on point cloud segmentation using a minimum spanning tree<br>应用最小生成树实现点云分割
%A Sun Jinhu
%A Zhou Laishui
%A An Luling
%A <br>孙金虎
%A 周来水
%A 安鲁陵
%J 中国图象图形学报
%D 2012
%I 
%X Point cloud segmentation is widely used in point cloud parameterization, shape recognition, and model editing. A point cloud segmentation algorithm based on a minimum spanning tree is proposed, which includes four steps: generating banded segmentation boundaries,region growing, splitting banded boundaries, and generating the final regions. The Snake model is used to extract the dividing lines, and the lines are expanded towards both sides to generate banded segmentation boundaries. Then the Minimum Spanning Tree is used to extract all interior points in each region using region growing. At the last step, the banded segmentation boundaries are split to several parts, and each part combined with its region to generate the final regions. Experiments show that the algorithm can avoid over segmentation or under segmentation and generate smooth segmentation boundaries. Compared with the Level Set segmentation algorithm, the algorithm can segment point cloud more efficiently.
%K point cloud
%K Snake model
%K model segmentation
%K minimum spanning tree
%K K-nearest neighbors
%K region growing<br>点云
%K 模型分割
%K Snake模型
%K 最小生成树
%K K邻域
%K 区域增长
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D06194629680C940ACE75262F54B9D85&aid=804D8F4691AB7856DC0364EAF6156028&yid=99E9153A83D4CB11&vid=BCA2697F357F2001&iid=DF92D298D3FF1E6E&sid=9596F7248FB5796B&eid=461E94ABCF58C63F&journal_id=1006-8961&journal_name=中国图象图形学报&referenced_num=0&reference_num=19