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. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
De Vieilleville, F., & Lachaud, J. O. (2009). Digital deformable model simulating active contours. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5810 LNCS, pp. 203–216). https://doi.org/10.1007/978-3-642-04397-0_18
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