Image segmentation is the process of partitioning a digital image into multiple segments to simplify the representation of an image into something that is more meaningful and easier to analyze. In this paper, various techniques of image segmentation are discussed and compared with the basic parameters. Medical images are generally characterized by multiple regions, and weak edges. When regions in medical images are made up of homogeneous group of intensities, it becomes more difficult to analyze because different organs or anatomical structures may have similar gray level or intensity representation. Practically Multi Thresholding, Correlation Matching, FCM, KFCM and PFCM have been evaluated and the results obtained shows that Multi Thresholding is the most efficient