Automated Method of Extracting Urban Roads Based on Region Growing from Mobile Laser Scanning Data
1
School of Geographic Information and Tourism, Chuzhou University, No. 1 Huifeng West Road, Chuzhou 239000, China
2
Department of Geomatics Engineering, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada
3
School of Geographical Sciences, Guangzhou University, No. 230, Waihuan West Road, Guangzhou 510006, China
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(23), 5262; https://doi.org/10.3390/s19235262
Received: 23 October 2019 / Revised: 23 November 2019 / Accepted: 28 November 2019 / Published: 29 November 2019
(This article belongs to the Special Issue LiDAR-Based Creation of Virtual Cities)
With the rapid development of three-dimensional point cloud acquisition from mobile laser scanning systems, the extraction of urban roads has become a major research focus. Although it has great potential for digital image processing, the extraction of roads using the region growing approach is still in its infancy. We propose an automated method of urban road extraction based on region growing. First, an initial seed is chosen under constraints relating to the Gaussian curvature, height and number of neighboring points, which ensures that the initial seed is located on a road. Then, the growing condition is determined by the angle threshold of the tangent plane of the seed point. Then, new seeds are selected based on the identified road points and their curvature. The method also includes a strategy for dealing with multiple discontinuous roads in a dataset. The result shows that the method can not only achieve high accuracy in urban road extraction but is also stable and robust.
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MDPI and ACS Style
Li, P.; Wang, R.; Wang, Y.; Gao, G. Automated Method of Extracting Urban Roads Based on Region Growing from Mobile Laser Scanning Data. Sensors 2019, 19, 5262.
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