Road extraction and intersection detection based on tensor voting

Abstract

Road is the skeleton of the city, which is usually elongated. Extracting road information is of great significance in urban planning. Tensor voting can detect the geometric characteristics of the typical objects in the image. In this paper in order to improve the accuracy of road extraction in high-resolution remote sensing image, road is extracted preliminary using morphological edge segmentation and shape index feature extraction, then tensor voting is introduced to purify the road information and detect road intersections. Voting in stick field can detect and amplify the stick saliency of road pixels, the gaps can also be connected after tensor voting. On the basis of pure road extraction result above, the voting in ball field is used to detect the road intersections. The experiments on remote sensing images show that the proposed method in this paper is superior to traditional morphological post-processing method, it can precisely extract the roads, and detect all the road intersections at the same time.