Skin disease analysis and tracking based on image segmentation

Tracking of the skin disease is a necessary step of diagnostic as well the measure of the wound´s surface is very useful in healing´s document. To overcome the difficulties of the skin illness´s estimation, encountered with the currently used measurement techniques, we propose a novel approach aiming to reduce the time-consuming and the error rate. The proposed method is based on two steps; the first step is a preprocessing one which consists in image segmentation to detect the edge of the infected skin region. In the second one, another proposed method is applied to measure the wound `size´ and control the illness evolution. In this work, a comparative study was realized to select the most suitable segmentation technique referred to a proposed criterion based on `edge accuracy´ EAC. The new criterion was compared with the `surface accuracy´ based on ROC¹ space. The experiments show the performance of the proposed criterion and the efficacy of the measurement technique.