Image Segmentation is a very important aspect of perception and it still a very thought provoking subject for machine and computer perception. Studies in computer vision proves that the segmenting an image into various understandable regions for subsequent post processing (e.g., scene understanding, pattern recognition) is an ambitious task. This paper discusses the major colour image segmentation approaches. Then we review various algorithms with their advantages and disadvantages which try to increase class distinguishability. We are using the Berkeley Segmentation dataset BSD300 for segmentation which contains natural colour images. Lastly summarize the image segmentation methods, developed to integrate more feature information with high accuracy.