IMPLEMENTING GMM-BASED HIDDEN MARKOV RANDOM FIELD FOR COLOUR IMAGE SEGMENTATION

As it is well known to all that the terms image segmentation means dividing a picture into different types of regions and classes of particular geometric shape. So we can say that each class has normal distribution with specific mean and variance and hence the picture can be a Gaussian Mixture Model. In this paper, we first study the Gaussian-based hidden Markov random field (HMRF) model and its expectation maximization (EM) algorithm. Then we generalize it to Gaussian mixture model-based hidden Markov random field. The algorithm is implemented in MATLAB R20013a. We also apply this algorithm to color image segmentation problems.