Perceptual Grouping and Active contour functions for the extraction of roads in satellite pictures

We present a new method for Perceptual Grouping of pixels into roads after crest lines detection in satellite pictures. First the visual properties expected from the groupings are modelled as a quality function similar to active contour functions. They involve curvature, grey levels and co-circularity. This function is computed recursively and optimized from a local to global level with an algorithm related to dynamic programming. The Fnal groupings are then selected according to their global quality. Applied to satellite images, the method proved its adaptability and its robustness to noisy environments. The results showed how the use of visual properties can provide an. effective segmentation with no prior knowledge of the scene. This segmentation can be used to initialize a high level interpretation process or give a first description of the scene to an interactive decision system.