BOND PERCOLATION-BASED GIBBS-MARKOV RANDOM-FIELDS FOR IMAGE SEGMENTATION

A new bond percolation-based approach is presented to determine the cl ique potential parameters of a Gibbs-Markov random field (GMRF) model used in image segmentation. Previously, experimentally determined fixe d values were used for these parameters independent of the underlying image, Using the proposed approach, these parameters are now derived a s 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 cli que potential parameters.