LiDAR Point Cloud Thinning Algorithm for Road Survey and Design

doi:10.13474/j.cnki.11-2246.2017.0316

Abstract

Abstract: When the traditional thinning algorithm is applied to data extraction of road point cloud, there are many defects, such as cannot take good account of terrain features, or appear the large area point cloud hole. In this paper, an improved algorithm based on mean curvature is proposed for the extraction of point cloud data in road survey and design. Firstly, the mean curvature of all points is obtained by local quadratic surface fitting. And then according to the mean curvature to determine the terrain features, and as the main criteria for the identification of point cloud data dilution. Finally, the problem of the large area point cloud hole in the flat road surface is solved by using the marking method. Through the experimental results and analysis, the reliability and applicability of the thinning algorithm are proved.

Key words: road survey and design, LiDAR, thinning, mean curvature, point cloud hole

CLC Number:

P237

FANG Chengxi, SUI Lichun, ZHU Haixiong. LiDAR Point Cloud Thinning Algorithm for Road Survey and Design[J]. 测绘通报, 2017, 0(10): 58-61,88.

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