Deformable models are continuous energy-minimizing techniques that have been successfully applied to image segmentation and tracking since twenty years. This paper defines a novel purely digital deformable model (DDM), whose internal energy is based on the minimum length polygon (MLP). We prove that our combinatorial regularization term has “convex” properties: any local descent on the energy leads to a global optimum. Similarly to the continuous case where the optimum is a straight segment, our DDM stops on a digital straight segment. The DDM shares also the same behaviour as its continuous counterpart on images.
Financed by the National Centre for Research and Development under grant No. SP/I/1/77065/10 by the strategic scientific research and experimental development program:
SYNAT - “Interdisciplinary System for Interactive Scientific and Scientific-Technical Information”.