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Global shape entropy: a mathematically tractable approach to building extraction in aerial imagery

This work presents an information theoretic approach to the problem of building extraction in aerial imagery. Boundary curvature is selected as a suitable measure of shape information and its relationship to Shannon's concept of entropy is discussed. A novel concept of global and local shape entropy is defined. A mathematically tractable approach to connected region growing is developed utilizing this novel concept of global shape entropy. An algorithm for the automatic extraction of building silhouettes in aerial imagery is presented. The algorithm is shown to be shape independent by successfully extracting rectangular buildings and a circular storage tank in real imagery. The limitations of the algorithm are discussed and possible future research is proposed.