Identification of Cancerous Lesions in Unconstrained Images

Abstract

The incidence of melanoma rises rapidly in Caucasians after the age of 20, and US statistics show about 1million new cases every year. Specialists in the field are highly accurate in determining whether a skin lesion is cancerous or not based solely on a visual inspection. No systems exist for accurately classifying skin spots.The first stage in the development of such a system is to identify the region of interest. This paper reviews approaches to using three edge detection algorithms for edge detection – and therefore extraction of the lesion from the surrounding skin.The three edge detection algorithms used are Sobel, Marr-Hildreth and Canny. Their performance is compared for 136images of both cancerous and non-cancerous lesions.Depending on the images, the best results are obtained either by Canny or by the Marr-Hildreth algorithm, however the edges produced by the latter are indistinct and the processing time is four times that of the other algorithms.