We propose an intersection model and strategy for automatic road extraction from aerial imagery. The proposed approach is able to detect typical intersections such as crossroads, T-junctions and Y-junctions based on matching the model to the image features. Compared to the traditional morphological methods, for example the combination with thinning and 8-neighbor pattern matching, our approach is less sensitive to noise and holes, and less like to produce a false match. The road network is constructed by connecting the detected intersections. The connecting hypothesis is generated and validated using the road tracking method and the road shape including the width is refined using ribbon snakes. We show the feasibility of our approach by presenting results for a suburban area, and evaluating them in comparison to the existing road map.
Go Koutaki, Keiichi Uchimura, Zhencheng Hu, "Automatic Road Extraction Based on Intersection Detection in Suburban Areas" in Journal of Imaging Science and Technology, 2005, pp 163 - 169, https://doi.org/10.2352/J.ImagingSci.Technol.2005.49.2.art00007