Road edge detection from remote sensing image based on improved Sobel operator
TAN Yuan1, HUANG Huixian1, XU Jianmin2, CHEN Ren1
1. College of Information Engineering, Xiangtan University, Xiangtan 411105, China;
2. School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510640, China
Extracting road edge from remote sensing image can extremely simplify the land survey workload for planning traffic networks. Because of the direction and size limitations of the template, the edge detection result derived by traditional algorithms shows high rate of false positive points and discontinuity, which is the reason why traditional edge detection algorithms can seldom achieve an ideal result in detecting continuous and integral road edge. To deal with this problem, this study proposes an improved Sobel operator which is based on an 8 directional 5×5 template. The optimal settings of each direction in the template are derived by the Pascal's triangle theory. The improved operator not only achieves a better performance of edge detection in different directions but reduces the false positive point effectively as well. In comparison with other operators, the improved Sobel operator proposed by this study has better integrity and continuity in road edge extraction results, especially in road curve detection.
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2016, Vol. 28 
