Effective Image Segmentation with Flexible ICM-Based Markov Random Fields in Distributed Systems of Personal Computers

摘要

This paper presents the implementation of modified Markov Random Fields (MRFs) in distributed systems of personal computers. Gibbs Random Fields (GRFs) operating in the iterated conditional mode(ICM), modified to incorporate the flexibility of selecting from a continuum of configurations ranging from greater fidelity to the original image to more contextual influence(and enhanced smoothing), are presented, implemented in a distributed system of personal computers, and assessed for image segmentation.