Color based image segmentation using different versions of k-means in two spaces

Abstract

In this paper color based image segmentation is done in two spaces. First in LAB color space and second in RGB space all that done using three versions of K-Means: K-Means, Weighted K-Means and Inverse Weighted K-Means clustering algorithms for different types of images: biological images (tissues and blood cells) and ordinary full colored images. Comparison and analysis are done between these three algorithms in order to differentiate between them.