Performance analysis of clustering based image segmentation and optimization methods

Abstract

Partitioning of an image into several constituent components is called image segmentation. Myriad algorithms using different methods have been proposed for image segmentation. Many clustering algorithms and optimization techniques are also being used for segmentation of 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 some image segmentation techniques are evaluated based on their consistency in different applications. Based on the parameters used quantification of different clustering algorithms is done. .