Non-Invasive Screening and Discrimination of Skin Images For Early Melanoma Detection

This paper presents an experimental investigation of human skin. Human skin is a complex surface, with fine scale geometry that makes its appearance difficult to model. Also, the conditions under which the skin surface is viewed and illuminated greatly affect its appearance and properties. It can be easily examined with the eyes, however, many particular as pects of the skin are better evaluated by non-invasive methods. Then it describes a method that helps in detection of suntanned or precancerous skin using gross-over all image segmentation. A skin cancer can become highly invasive and lethal if not treated at the earliest possible stage and it aims to eliminate the need for a patient to under go biopsy as a means of basic diagnosis for melanoma. Generally UV rays from the sun and other sources can damage skin cells causing cells to grow abnormally. Melanoma is considered as one such dangerous type of skin cancer. The main cause of melanoma is excessive exposure to UV radiation reaching the skin. When compared to the normal skin the structure of abnormal skin as an irregular outer epidermal layer as well as the inner dermal layer. Skin cancer can be detected using ABCB rule with good diagnostic accuracy as it is easy to detect melanoma by ABCD parameters. In this paper all types of skin can be tested viz normal skin, suntanned and pre -cancerous as well as it diagnosis the freckle(mole) and congenital nevi(moles that appear at birth).