摘要
针对植被点影响三维激光扫描仪获取开采沉陷盆地精度的问题,提出一种基于点云均匀度的树木点剔除方法。首先构建以点k-邻域的最大坐标差为边长的虚拟立方体,以及包围该点集的最小长方体,通过最小长方体与虚拟立方体的体积比来判别植被点。研究结果表明,该方法可较好的识别树木和低矮的杂草等植被点,可以提高开采沉陷盆地的精度。
Aimed at the problem of the influence on requiring mining subsidence basin precision with 3- D laser scanner conducted by vegetation point. A method of elimination of vegetation is proposed on the basis of uniformity of point cloud. Firstly, a virtual cube taking the maximum coordinate difference of the kneighborhood of point as the length and a minimum cuboid containing the points in the virtual cube were constructed. Through comparing the volume ratio of minimum cuboid and virtual cube, we can identify vegetation point. As the result showing, this method can improve the mining subsidence basin precision better by eliminating trees and low weeds point.
出处
《中国矿业》
北大核心
2016年第5期138-140,145,共4页
China Mining Magazine
基金
国家自然科学基金项目资助(编号:51504239)
江苏高校优势学科建设工程项目资助(编号:SZBF2011-6-B35)
关键词
三维激光扫描
沉陷盆地
均匀度
虚拟立方体
植被点
3-D laser scanning
subsidence basin
uniformity
virtual cube
vegetation point
