There are a number of different quantitative models that can be used in a medical diagnostic decision support system. The complexity of the diagnostic task is thought to be one of the prime determinants of model selection. Using histogram equalisation the input image is pre-processed and segment the suspicious portion from the image based on markov random field algorithm for segmentation method. Features are extracted based on texture, fractal and histogram features, finally the classification is done by using the support vector machine approach