SVM Classifier Based Melanoma Image Classification Kulkarni Atul1, Dr. Mukhopadhyay Debajyoti2 1Research Scholar, Information Technology, AMET University, Chennai 2Department of Computer Science, Maharashtra Institute of Technology, Chennai Corresponding Author E-mail:
Online published on 26 March, 2018. Abstract Melanoma Classification is the most important aspect that is related to the patients who endures melanoma. The melanoma is usually known by measuring the depth given in millimeters (mm) and is evaluated by the pathological assessment. In order to avoid the interference method usage in the surgery, a method is proposed for computational image analysis. In the system the Gray Level Co-occurrence Matrix (GLCM) and Local Binary Pattern (LBP) algorithms are used for the features extraction process and those features are classified by using the Support Vector Machine (SVM) classifier. The proposed melanoma classification gives the output accuracy of about 96.7% of classification accuracy value. Top Keywords Melanoma, dermoscopic, GLCM, LBP, etc. Top |