A Methodology for the Performance Analysis of Cluster Based Image Segmentation

Partitioning of an image into several constituent components is called image segmentation. Numerous algorithms using different approaches have been proposed for image segmentation. Today many data clustering algorithms are being used for segmenting images. A major challenge in segmentation evaluation comes from the fundamental conflict between generality and objectivity. As there is a glut of image segmentation techniques available today, customer who is the real user of these techniques may get obfuscated. In this paper to address the above described problem a review is done on different types of clustering methods used for image segmentation. Also a methodology is proposed to classify and quantify different clustering algorithms based on their consistency in different applications. This paper also describes the various performance parameters on which consistency will be measured in the proposed