Image Segmentation Based on Gabor Filter and MRF Model

This paper proposed a Gabor filter and MRF model for image segmentation. First, extract color features through transformation of color space; second, get image texture through Gabor filtering and Gaussian smoothing of the original color texture image; and then set up MRF image segmentation model, combining the color and texture features, to calculate the maximum posterior probability(MAP), and using ICM algorithm to optimize the computing complexity. We also proposed parameters estimation method using EM algorithm. Experiment shows that this mixture feature model is efficient than using only color or texture features.