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Open AccessArticle

Automated Method for Detection of Missing Road Point Regions in Mobile Laser Scanning Data

1
School of Transportation, Southeast University, 2 Southeast Univ. Rd, Nanjing, China
2
Department of Civil Engineering, Ryerson University, Toronto, ON M5B 2K3, Canada
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(12), 525; https://doi.org/10.3390/ijgi8120525
Received: 18 September 2019 / Revised: 13 November 2019 / Accepted: 23 November 2019 / Published: 25 November 2019
The paper proposes a method supported by MATLAB for detection and measurement of missing point regions (MPR) which may cause severe road information loss in mobile laser scanning (MLS) point clouds. First, the scan-angle thresholds are used to segment the road area for MPR detection. Second, the segmented part is mapped onto a binary image with a pixel size of ε through rasterization. Then, MPR featuring connected 1-pixels are identified and measured via image processing techniques. Finally, the parameters regarding MPR in the image space are reparametrized in relation to the vehicle path recorded in MLS data for a better understanding of MPR properties on the geodetic plane. Tests on two MLS datasets show that the output of the proposed approach can effectively detect and assess MPR in the dataset. The ε parameter exerts a substantial influence on the performance of the method, and it is recommended that its value should be optimized for accurate MPR detections.
Keywords: occlusion; missing points; mobile laser scanning; point cloud; image processing occlusion; missing points; mobile laser scanning; point cloud; image processing
MDPI and ACS Style

Ma, Y.; Zheng, Y.; Easa, S.; Hou, M.; Cheng, J. Automated Method for Detection of Missing Road Point Regions in Mobile Laser Scanning Data. ISPRS Int. J. Geo-Inf. 2019, 8, 525.

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