Alpha Markov Measure Field model for probabilistic image segmentation

We apply the theory of metric-divergences between probability distributions and a variational approach in order to obtain a new model for probabilistic image segmentation. We study a specific model based on a very general measure between discrete probability distributions. We show experimentally that this model is competitive with some other models of the state of the art. In this work we use a particular case of the the measure of kind between two discrete probability distributions.