Beta-Measure for Probabilistic Segmentation

We propose a new model for probabilistic image segmentation with spatial coherence through a Markov Random Field prior. Our model is based on a generalized information measure between discrete probability distribution (βMeasure). This model generalizes the quadratic Markov measure field models (QMMF). In our proposal, the entropy control is achieved trough the likelihood energy. This entropy control mechanism makes appropriate our method for being used in tasks that require of the simultaneous estimation of the segmentation and the model parameters.