Adaptive Snakes for Urban Road Extraction

For quickly populating GIS database, it is important to derive accurate and truly road information from imagery. In this paper, we describe the problem of urban road extraction from digital imagery using adaptive active contour models (Snakes). Our road extraction processing has three steps. First, we segment the image based on the dominant road directions. Second, we detect the road lines with the so called ‘acupuncture method ’. Finally, we refine the road edges by applying adaptive snakes to the corner desired approximation to extract the city block. During the process, we assume that the road network and block pattern in the city have a semi-regular grid pattern. For detecting the road lines, we exploit the distribution of edges in an urban area. Linear associated with roads are detected and these become the basis for initial approximations to road grid pattern for snakes based refinement. In order to accommodate variable line characteristics, we have developed an adaptive algorithm which locally modifies the weight of the energy terms. These ideas are applied to same actual urban imagery and the results are displayed and evaluated.