Regularized color clustering in medical image database

A regularized color clustering algorithm is proposed to solve the color clu stering problem in medical image database, By incorporating both measures o f cluster separability and cluster compactness, regularized color clusterin g allows the automatic extraction of significant color groups with varying populations. Experimental results in different color spaces show that the r egularized color clustering gives superior results in extracting significan t distinct/abnormal color clusters without significant increases in cluster compactness. Furthermore, results of color clustering in different color s paces show that the LUV color space is more suitable for color clustering. Methods for selecting the regularization constants have also been suggested .