基于表面特征差异的车载点云道路坑槽提取方法  

Road Pit Extraction Method Based on Surface FeatureDifference of Vehicle-borne Point Cloud

作　　者：安卫[1] AN Wei(Tianjin Surveying and Mapping Institute Co.,Ltd.,Tianjin 300380,China)

机构地区：[1]天津市测绘院有限公司,天津300380

出　　处：《测绘与空间地理信息》2023年第1期169-171,176,共4页Geomatics & Spatial Information Technology

摘　　要：为克服图像提取道路坑槽的局限性,本文提出一种基于车载点云表面特征差异的道路坑槽提取方法。该方法在完成原始点云预处理的基础上,基于最优邻域选择构建点云表面特征并分析表面特征变化趋势,结合点云表面特征差异分割提取道路坑槽初始三维点云数据,最后基于聚类分析的方法获取坑槽点云。实验结果表明:该方法能够准确从路面点云数据中提取路面坑槽,获取坑槽三维点云数据,为道路坑槽定量评价提供一种新的方法。In order to overcome the limitations of image extraction of road pits,a road pit extraction method based on the surface feature difference of vehicle-borne point cloud is proposed.On the basis of completing the preprocessing of the original point cloud,this method constructs the point cloud surface features based on the optimal neighborhood selection,analyzes the change trend of the surface features,extracts the initial three-dimensional point cloud data of the road pit combined with the difference segmentation of the point cloud surface features,and finally obtains the pit point cloud based on the cluster analysis method.The experimental results show that this method can accurately extract pavement pits from pavement point cloud data and obtain three-dimensional point cloud data of pits,which provides a new method for quantitative evaluation of road pits.

关 键 词：道路坑槽 车载LiDAR 表面特征 最优邻域 特征差异 

分 类 号：P225[天文地球—大地测量学与测量工程]