Research on Automatic Extraction of Road Pits Based on Carborne LiDAR Point Cloud Data
Taking the road point cloud data acquired by carborne LiDAR as the research object,a pit extraction method based on point cloud profile characteristic description is proposed. Firstly,the original point cloud data is filtered to obtain the surface point data;secondly,the contour fitting of Douglas Puck algorithm is carried out for the transverse and longitudinal sections of the road,and the integral invariance and differential characteristics are used as the description algorithm to extract the pits;finally,constraint conditions are used to cluster point clouds to eliminate noise points,further identify,determine and extracts pits. In order to verify the effective-ness of this method,we use a section of road point cloud data for experiments,and the results show that this method can effectively ex-tract the road surface pit points,which is not limited by the pit shape,and has high accuracy.
万方数据
维普
