Classification of dermatological ulcers based on tissue composition and color texture features

Abstract

We present color image processing methods for the analysis of images of dermatological lesions. The intended application is classification and analysis of the tissue composition of skin lesions or ulcers, in terms of granulation (red), fibrin (yellow), necrotic (black), callous (white), and mixed tissue composition. The images were analyzed and classified by an expert dermatologist into the classes mentioned above. Indexing of the images was performed based on statistical texture features derived from cooccurrence matrices of the RGB, HSV, L*a*b*, and L*u*v* color components. The classification was performed using different classifiers and database organization methods. The performance of classification was measured in terms of the area under the receiver operating characteristic curve, with values of up to 0.98 for the granulation and fibrin classes.