Bond Percolation-B ased Gibbs-Markov Random Fields for Image Segmentation

A new bond percolation-based approach is presented to determine the clique potential parameters of a Gibbs-Markov random field (GMRF) model used in image segmentation. Pre- viously, experimentally determined fixed values were used for these parameters independent of the underlying image. Using the proposed approach, these parameters are now derived as a function of local characteristics of the image under consideration. An additional salient feature of this method is its suitability for a renormalization group approach to multi-scale description of the clique potential parameters.