Expressway Surface Point Extraction from Mobile Laser Scanning Point Clouds

Abstract

According to the problem between the cost of production, efficiency and data accuracy of expressway surface terrain data, this paper presents a fast ground point extraction method of expressway road surface from mobile laser scanning (MLS) point cloud data. Through the analysis of the spatial characteristics of MLS point cloud data in expressway, a triangle plane constraint (TPC) method is used to extract initial road surface points in the grid, and then multi-scale neighborhood iterative analysis (MNIA) method is proposed to further filter them, finally the high density road surface points are extracted from the original points based on neighborhood slope which is estimated by iterative least square within eight neighboring grid. Experiments are processed to verify the effectiveness of the algorithm by using two groups of actual point cloud data.