Filtering of LiDAR Point Cloud Data Based on new TIN Algorithm

DOI

10.2991/icmse-17.2017.14How to use a DOI?

Keywords

LiDAR; point cloud; improved TIN; ground points; filtering; morphology

Abstract

In this paper, the new method is proposed for filtering of airborne LiDAR data based on improved Triangulated Irregular Network(TIN) algorithm and the details of filter principle is described. Firstly, LiDAR point cloud data is organized and designed by regular grid and TIN, the seed points from point cloud data are selected by regional sub-block method or mathematical morphology. Then, an initial sparse TIN is created from the seed points and densified upward gradually and the ground points are extracted through an interactive process. In experiments it is shown that this filtering method can effectively remove different sizes of buildings, low vegetation and other objects, and keep topographical features better.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Lichun Sui
AU  - Jianfeng Zhu
AU  - Haixiong Zhu
AU  - Mianqing Zhong
PY  - 2017/04
DA  - 2017/04
TI  - Filtering of LiDAR Point Cloud Data Based on new TIN Algorithm
BT  - Proceedings of the 2017 7th International Conference on Manufacturing Science and Engineering (ICMSE 2017)
PB  - Atlantis Press
SP  - 72
EP  - 76
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmse-17.2017.14
DO  - 10.2991/icmse-17.2017.14
ID  - Sui2017/04
ER  -