Volume XL-7/W4
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W4, 99-102, 2015
https://doi.org/10.5194/isprsarchives-XL-7-W4-99-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W4, 99-102, 2015
https://doi.org/10.5194/isprsarchives-XL-7-W4-99-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

  26 Jun 2015

26 Jun 2015

Segmentation-Based Ground Points Detection from Mobile Laser Scanning Point Cloud

X. Lin and J. Zhang X. Lin and J. Zhang
  • Institute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping, Beijing 100830, China

Keywords: Filtering, Mobile Laser Scanning, Point Cloud, Point Cloud Segmentation

Abstract. In most Mobile Laser Scanning (MLS) applications, filtering is a necessary step. In this paper, a segmentation-based filtering method is proposed for MLS point cloud, where a segment rather than an individual point is the basic processing unit. Particularly, the MLS point cloud in some blocks are clustered into segments by a surface growing algorithm, then the object segments are detected and removed. A segment-based filtering method is employed to detect the ground segments. Two MLS point cloud datasets are used to evaluate the proposed method. Experiments indicate that, compared with the classic progressive TIN (Triangulated Irregular Network) densification algorithm, the proposed method is capable of reducing the omission error, the commission error and total error by 3.62%, 7.87% and 5.54% on average, respectively.