Skin is the outermost and largest organ of the human body that protects us from the external agents. Among the various types of diseases affecting the skin, melanoma (skin cancer) is the most dangerous and deadliest disease. Though it is one of the dangerous forms of cancer, it has a high survival rate if and only if it is diagnosed at the earliest. In this study, skin cancer classifi cation (SCC) system is developed using dermoscopic images. It is considered as a classifi cation problem with the help of Bendlet Transform (BT) as features and Support Vector Machine (SVM) as a classifi er.First, the unwanted information's such as hair and noises are removed using median fi ltering approach. Then, directional representation based feature extraction system that precisely classifi es curvature, location and orientation is employed. Finally, two SVM classifi ers are designed for the classifi cation. The performance of the SCC system based on Bendlet is superior to other image representation systems such as Wavelets, Curvelets, Contourlets and Shearlets.
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