Dempster-Shafer's theory as an aid to color information processing. Application to melanoma detection in dermatology

In this paper, we first propose a color image segmentation method based on the Dempster-Shafer theory. The tristimuli R, G and B are considered as three independent information sources which can be very limited or weak. The basic idea consists of modeling the color information in order to have the features of each region in the image. This model, obtained on training sets extracted from the intensity, allows us to reduce the classification errors concerning each pixel of the image. The proposed segmentation algorithm has been applied to biomedical images in order to detect a kind of skin cancer (melanoma). In a second step, features concerning the lesion are extracted using color information. These features are used in order to classify the benign lesions (naevus) from the other. Results, including the management of false alarms and no detections, allow us to demonstrate the effectiveness of the proposed methodology.