Publication

Abstract : A fatalform of skin cancer is Melanoma and the fifth most common cancer in the world. It is responsible for the majority of deaths due to skin cancer. Treating and diagnosing melanoma at the initial stages is very crucial as cancer may spread to other organs in the body very quickly which makes it more difficult to treat and may be fatal. Various techniques have been developed for early detection of melanoma like dermatoscopy and it is essential to find the correct set of features and machine learning techniques for classification. The objective of the paper is to exhibit common machine learning algorithms used which is Artificial Neural Network (ANN) and Support Vector Machine (SVM) and techniques of Discrete Wavelet Transform (DWT) that is utilized for feature selection and Gray Level Co-Occurrence Matrix (GLCM) that is implied in feature extraction. The intent of the paper is to show the advantages of using the SVM classifier for the detection of melanoma.