Color identification in dermoscopy images using Gaussian mixture models

Development of Computer Aided Diagnosis systems that mimic the performance of dermatologists when diagnosing dermoscopy images is a challenging task. Despite the relevance of color in the diagnosis of melanomas, few of the proposed systems exploit this characteristic directly. In this paper we propose a new methodology for color identification in dermoscopy images. Our approach is to learn a statistical model for each color using Gaussian mixtures. The results show that the proposed method performs well, with an average Spearman correlation of 0.7981, with respect to a human expert.