MELANOMA IMAGE CLASSIFICATION SYSTEM BY NSCT FEATURES AND BAYES CLASSIFICATION

Abstract

The knowledge obtained from a classification system is increasingly important for making a final decision. In this paper, a skin cancer classification system using Non-Sub sampled Contourlet Transform (NSCT) is presented. It uses double iterated filter banks to detect point discontinuities by a Laplacian pyramid and directional features by a directional filter bank. It allows the approximation of given image into a smooth contour at various level of decomposition. The Bayesian classifier is utilized in this work to classify the dermoscopic images in the PH2 database into normal or abnormal. From the results of the system, the melanoma image classification system can be used as a tool to make a final decision for the physicians.