Paper Details

Melanoma is the deadliest form of skin cancer. Incidence rates of melanoma have been increasing, especially among nonHispanic white males and females, but survival rates are high if detected early. Due to the costs for dermatologists to screenevery patient, there is a need for an automated system to assess a patient’s risk of melanoma using images of their skinlesions captured using a standard digital camera. One challenge in implementing such a system is locating the skin lesion inthe digital image. A novel texture-based skin lesion segmentation algorithm is proposed. A set of representative texturedistributions are learned from an illumination-corrected photograph and texture distinctiveness metric is calculated for eachdistribution. Next, regions in the image are classified as normal skin or lesion based on the occurrence of representativetexture distributions. The proposed segmentation framework is tested by comparing lesion segmentation results andmelanoma classification results to results using other state-of-art algorithms. The proposed framework has highersegmentation accuracy compared to all other tested algorithms.

Mrs. C.Gomathi, A.Mala, “TRE Technique Based Dermoscopic Image Segmentation of Skin Lesions for Skin Cancer”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 4, Issue 4, pp. 1140-1145, April 2017.