A comparison study of different color spaces in clustering based image segmentation

Abstract

In this work we carry out a comparison study between different color spaces in clustering-based image segmentation. We use two similar clustering algorithms, one based on the entropy and the other on the ignorance. The study involves four color spaces and, in all cases, each pixel is represented by the values of the color channels in that space. Our purpose is to identify the best color representation, if there is any, when using this kind of clustering algorithms. © Springer-Verlag Berlin Heidelberg 2010.