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Ground filtering algorithm for mobile LIDAR using order and neighborhood point information

Siyuan Huang (Department of Electronic and Optical Engineering, Army Engineering University, Shijiazhuang Campus, Shijiazhuang, China)
Limin Liu (Department of Electronic and Optical Engineering, Army Engineering University, Shijiazhuang Campus, Shijiazhuang, China)
Jian Dong (Department of Electronic and Optical Engineering, Army Engineering University, Shijiazhuang Campus, Shijiazhuang, China)
Xiongjun Fu (School of Information and Electronics, Beijing Institute of Technology, Beijing, China)
Leilei Jia (Department of Electronic and Optical Engineering, Army Engineering University, Shijiazhuang Campus, Shijiazhuang, China)

Engineering Computations

ISSN: 0264-4401

Article publication date: 23 September 2020

Issue publication date: 17 June 2021

162

Abstract

Purpose

Most of the existing ground filtering algorithms are based on the Cartesian coordinate system, which is not compatible with the working principle of mobile light detection and ranging and difficult to obtain good filtering accuracy. The purpose of this paper is to improve the accuracy of ground filtering by making full use of the order information between the point and the point in the spherical coordinate.

Design/methodology/approach

First, the cloth simulation (CS) algorithm is modified into a sorting algorithm for scattered point clouds to obtain the adjacent relationship of the point clouds and to generate a matrix containing the adjacent information of the point cloud. Then, according to the adjacent information of the points, a projection distance comparison and local slope analysis are simultaneously performed. These results are integrated to process the point cloud details further and the algorithm is finally used to filter a point cloud in a scene from the KITTI data set.

Findings

The results show that the accuracy of KITTI point cloud sorting is 96.3% and the kappa coefficient of the ground filtering result is 0.7978. Compared with other algorithms applied to the same scene, the proposed algorithm has higher processing accuracy.

Research limitations/implications

Steps of the algorithm are parallel computing, which saves time owing to the small amount of computation. In addition, the generality of the algorithm is improved and it could be used for different data sets from urban streets. However, due to the lack of point clouds from the field environment with labeled ground points, the filtering result of this algorithm in the field environment needs further study.

Originality/value

In this study, the point cloud neighboring information was obtained by a modified CS algorithm. The ground filtering algorithm distinguish ground points and off-ground points according to the flatness, continuity and minimality of ground points in point cloud data. In addition, it has little effect on the algorithm results if thresholds were changed.

Keywords

Citation

Huang, S., Liu, L., Dong, J., Fu, X. and Jia, L. (2021), "Ground filtering algorithm for mobile LIDAR using order and neighborhood point information", Engineering Computations, Vol. 38 No. 4, pp. 1895-1919. https://doi.org/10.1108/EC-04-2020-0198

Publisher

:

Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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