Buildings are regarded as the most prominent man-made objects: hence, their automatic extraction from aerial and satellite images has attracted the interest of photogrammetric research communities. In this paper, a balloon snake, a well-known active contour model, was developed for the precise extraction of building boundaries. Traditional active contours are highly sensitive to image data and are problematic when building boundaries are weakened, usually due to occlusions. To improve the efficiency of the traditional balloon snake model, a shape-based balloon snake model was introduced where knowledge about the expected geometrical shape of buildings was modeled and applied to the traditional snake representation. Implementation of the proposed algorithm confirmed its efficiency in the precise extraction of building boundaries. Experimental results and the qualitative and quantitative evaluations demonstrate the potential of the proposed shape-based balloon snake model and its superiority over traditional models.
