Gabor-MRF Model Based on Color Texture Image Segmentation

We propose a Gabor filter and Markov random fields(MRF)-based method for color texture image segmentation.First,we analyze color and texture feature,transforme RGB space to LUV space to get color feature vector,and then do Gabor filtering and Gaussian smoothing processing on original color image and MRF model is used to represent the regional relationship.Finally,we combine color and texture information and use Bayesian method to estimate maximum a Posteriori(MAP).The experimental results show that this algorithm is efficiently doing color texture image segmentation.