TITLE:
A Road Extraction Method Based on Region Growing and Mathematical Morphology from Remote Sensing Images
AUTHORS:
Yunhe Liu, Chi Ma, Li Li, Xiaoyan Xing, Yong Zhang, Zhigang Wang, Jiuwei Xu
KEYWORDS:
Region Growing, Mathematical Morphology, Road Extraction, Remote Sensing Images
JOURNAL NAME:
Journal of Computer and Communications,
Vol.6 No.11,
November
19,
2018
ABSTRACT: Road traffic is the important driving factor for economic and social development. With the rapid increase of vehicle population, road traffic problems such as traffic jam and traffic accident have become the bottleneck which restricts economic development. In recent years, natural disasters frequently occur in China. Therefore, it is essential to extract road information to compute the degree of road damage for traffic emergency management. A road extraction method based on region growing and mathematical morphology from remote sensing images is proposed in this paper. According to the road features, the remote sensing image is preprocessed to separate road regions from non-road regions preliminarily. After image thresholding, region growing algorithm is used to extract connected regions. Then we sort connected regions by area to exclude the small regions which are probably non-road objects. Finally, the mathematical morphology algorithm is used to fill the holes inside the road regions. The experimental results show that the method proposed can effectively extract roads from remote sensing images. This research also has broad prospects in dealing with traffic emergency management by the government.