Colour image segmentation using fuzzy clustering techniques

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. Fuzzy clustering is one of the methods used for image segmentation. This paper describes two fuzzy clustering methods to analyze and segment the color space. The clustering algorithms, namely, Fuzzy c means algorithm(FCM) and Possibilistic c means algorithm(PCM) are used for image segmentation. A self estimation algorithm has been developed for determining the number of clusters. The quality of the segmented image is estimated by their Peak Signal to noise ratio(PSNR).