Image segmentation [1] is the process of partitioning a digital image into several segments, i.e. sets of pixels. Image segmentation by considering the textural property of anatomical structures and regions of interest plays a crucial role in most medical imaging applications. Texture refers to properties that represent the surface or structure of an object. Feature extractions, texture discrimination, texture classification, shape from texture are the major problems in texture analysis. The segmented image is more meaningful and easier to analyze. Medical imaging is the technique and process used to create images of the human body for clinical purposes (diagnosing or examining disease). In reality, these images are rich in color and texture. It is difficult to identify image regions containing color-texture patterns. Color is that attribute of light energy that is related to wavelength. It is well known that color conveys a very important part of information regarding the objects of interest in an image. This concept is used in color-based segmentation [9] of images. For ...