Urban Road Network Extraction Based on Fuzzy ART, Radon Transform and Morphological Operations on DSM Data
In urban areas, the main disadvantage of an aerial photo for road extraction is the shadow cast by buildings and the complexity of the road network. For this case, we used Digital Surface Model (DSM) data, which are based on the elevation of land surfaces. However, one of the problems associated with DSM data is the non-road area with the same road elevations, like parking places, parks, empty ground and so on. In this paper, we propose the Mixed ART clustering on histogram followed by region growing to extract the initial road and perform the road filter by opening operation with a line shape structuring element, where the line orientation is obtained from the Radon Transform. Finally, the road networks are constructed based on B-Spline curve from the skeleton of the extracted road. The experimental result shows that the proposed method improved the quality and the accuracy average within an acceptable time.
Keywordsroad extraction ART clustering region growing Radon transform morphological operations
- 2.Maurya, R., Shalini, S., Gupta, P.R., Manis, K.S.: Road extraction using k-means clustering and morphological operations. International Journal of Advanced Engineering Sciences and Technologies 5(2), 290–295 (2011)Google Scholar
- 9.Heipke, C., Mayer, H., Wiedemann, C., Jamet, O.: Evaluation of Automatic Road Extraction. International Archives of Photogrammetry and Remote Sensing 32(3-2W3), 47–56 (1997)Google Scholar