激光与光电子学进展, 2018, 55 (7): 071006, 网络出版: 2018-07-20   

利用邻近点几何特征实现建筑物点云特征提取 下载: 709次

Feature Extraction of the Building Point Cloud by Using Geometrical Characteristics of Adjacent Points
董伟 *
作者单位
中铁第四勘察设计院集团有限公司, 湖北 武汉 430063
摘要
三维激光扫描的点云中包含了大量数据,而其中有些数据在应用过程中并不都能产生作用,特别是对于建筑物点云而言,只需要确定建筑物轮廓线上的点云即可。基于此,本文利用邻近点几何特征来实现建筑物点云特征线的提取。该算法首先利用k最近邻搜索算法,对某个点的邻近点进行搜索,并根据邻近点确定法向量及基准面,利用基准面上探测点和邻近点的法向量夹角特性,确定建筑物边界;其次利用整体最小二乘和加权主元分析法对随机抽样一致算法进行改进,并基于该改进算法,确定折边两侧点云平面,利用两侧点云边界特性探测建筑物折边。通过实例分析,可以确定该算法提取速度快、冗余度少,在无效点云剔除率高于90%的情况下,提取了建筑物的特征线。
Abstract
The point cloud scanned by terrestrial laser scanning contains mass data. Not all of these data are useful in the process of application, especially for the building point cloud, the building can be described when the building profile is determined. Therefore, the geometrical characteristics of adjacent points are used to extract features of the building point cloud. Firstly, the proposed algorithm uses the k-nearest neighbor search algorithm to search the adjacent points of one point. The normal vector and datum plane are determined according to the adjacent points. The characteristics of normal vector angle between the probe points and the adjacent points are used to determine the building boundary. Secondly, the total least squares and weighted principal component analysis are used to improve the random sample consensus algorithm. The point clouds on both sides of the fold boundary are determined by the improved algorithm. The characteristics of boundary are used to probe the building fold edge. The results show that the proposed algorithm is fast and less redundancy, and can be used to extract feature lines of the building with more than 90% eliminating rate of the invalid point cloud.

董伟. 利用邻近点几何特征实现建筑物点云特征提取[J]. 激光与光电子学进展, 2018, 55(7): 071006. Dong Wei. Feature Extraction of the Building Point Cloud by Using Geometrical Characteristics of Adjacent Points[J]. Laser & Optoelectronics Progress, 2018, 55(7): 071006.

本文已被 4 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!