Minimal stochastic complexity snake-based technique adapted to an unknown noise model.


We propose a polygonal snake segmentation technique adapted to objects that can be composed of several regions with gray-level fluctuations described by a priori unknown probability laws. This approach is based on a histogram equalization and on the minimization of a criterion without parameter to be tuned by the user. We demonstrate the efficiency of this… (More)


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