Skin cancer is by far the most common type and fastest growing cancer in recent years. There are three major types of skin cancer, they are basal cell carcinoma, squamous cell carcinoma and melanoma. Melanoma is considered as the most dangerous form of skin cancer, because it’s much more likely to spread to other parts of the body, it becomes more difficult to treat and can be deadly. The medical image processing plays a significant role in clinical diagnosis of different diseases. The image processing technique is used to classify melanoma or nevus from the skin. The steps involved are collecting Dermoscopy images database, pre-processing, segmentation using threshold, statistical feature extraction using Gray Level Co-occurrence Matrix (GLCM), Local Binary Pointer (LBP), Asymmetry, Border, Color, Diameter (ABCD Parameters) etc. and feature classification using Support Vector Machine (SVM). This technique provides an automatic image analysis tool for an accurate and fast evaluation of the lesion. The results show that the classification accuracy is