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We present a Markov random field model for image binary segmentation that computes the probability that each pixel belongs to a given class. We show that the computation of a real valued field has noticeable computational and performance advantages with respect to the computation of binary valued field; the proposed energy function is efficiently minimized with standard fast linear order algorithms...
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