An algorithm of scenes description and analysis based on MRF

Markov random fields (MRF) can be used for a wide variety of vision problems. In this paper we will propose an algorithm of scenes feature description and analysis based on MRF. The theoretical framework is based on MRF and Bayesian estimation via the energy optimization. We analyze the texture feature. Using MRF to modeling on the image, then combine with texture information and use of Bayesian to obtain the energy function, through the iterative optimization algorithm to minimize the energy function. Experimental results will be provided to illustrate the performance of our method.