Efficient Image Segmentation Method Based on Probabilistic Markov Random Field Model

In this paper, we present a new approach to image segmentation that is based on Markov random fields and Maximum a posteriori rule. Segmentation of an image is a challenging task especially in low contrast images, blurred images and noisy images. Most of the segmentation techniques are based only on the gray scale intensity of the image and yield poor results when applied to images with sophisticated background and high degree fuzziness. The MRF based segmentation method gives a priori information of the local structure contained in the image to get better segmentation accuracy. This proposed algorithm gives a promising solution to image segmentation and it is also robust to noise and blur.