Color image segmentation using k-means clustering and Optimal Fuzzy C-Means clustering

Segmentation of an image entails the division or separation of the image into regions of similar attribute. The most basic attribute for segmentation of an image is its luminance amplitude for a monochrome image and color components for a color image. Clustering is one of the methods used for segmentation. The objective of this paper is to compare the performance of various segmentation techniques for color images. K-means clustering and Optimal Fuzzy C-Means clustering techniques are compared for their performance in segmentation of color images.