Image Segmentation Based on Local Region Energy Minimization Model

This paper presents local region energy minimization model based on Markov Random Field(MRF) and probabilistic theory.The model converts traditional segmentation based on pixel into that based on region.It can reduce misclassification rate among the smooth area.The model is compared with the MRF model using ICM algorithm,Gibbs sampler algorithm and Metropolis sampler algorithm to segment image.Results show that the proposed energy model is able to obtain more accurate segmentation result and also can effectively restrain effect of image noise and texture for segmentation.