JOURNAL ARTICLE

A Road Extraction Method Based on Region Growing and Mathematical Morphology from Remote Sensing Images

Yunhe LiuChi MaLi LiXiaoyan XingYong ZhangZhigang WangJiuwei Xu

Year: 2018 Journal:   Journal of Computer and Communications Vol: 06 (11)Pages: 91-97   Publisher: Scientific Research Publishing

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.

Keywords:
Mathematical morphology Bottleneck Thresholding Computer science Geography Transport engineering Region growing Remote sensing Population Artificial intelligence Image (mathematics) Image segmentation Image processing Engineering

Metrics

2
Cited By
0.00
FWCI (Field Weighted Citation Impact)
2
Refs
0.18
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Automated Road and Building Extraction
Physical Sciences →  Engineering →  Ocean Engineering
Remote-Sensing Image Classification
Physical Sciences →  Engineering →  Media Technology
Remote Sensing and Land Use
Physical Sciences →  Earth and Planetary Sciences →  Atmospheric Science

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