Road Extraction Based on Snakes and Sophisticated Line Extraction

The extraction of roads from aerial and satellite images is an important task within cartography and planning of new road networks. The automation of this task is highly motivated by the expected increase of the speed and the precision of extraction. This work considers automatic road extraction from single aerial images of high resolution. It is based on two previously developed approaches: The first one is the differential geometric approach for extraction of linear features; The second contour extraction based on Active Contour Models, also called snakes. Whereas the first approach is fully-automatic, the second was previously mostly used for semi-automatic tasks which require the control of a human operator. This work combines both techniques and adapt them in the method for fully-automatic road extraction. According to the used strategy, the hypotheses for most salient roads in images of rural scenes are generated and verified first. Then, based on the ends of extracted roads the hypotheses for other roads are stated. The developed snake-based technique for the verification of these hypotheses enables recognition of partially occluded and shadowed roads as well as some roads passing through road crossings. The presented results of the developed approach show that the reliable extraction of roads which images are disturbed by surrounding objects is in many cases possible without the explicit knowledge about these objects. This is a big advantage since the automatic recognition of buildings, vegetation etc., is a very complicated problem by itself.