Melanoma is the most deadly form of cancer which is easily curable if detected at the earlier stage. The main objective of this paper is to classify the Melanoma and Non-melanoma using dermoscopy images from the Med Node Dataset. The images are enhanced by bottomhat filter, and then segmentation is done by two methods 1. Morphological Operations, 2. Otsu Thresholding. The features extracted from the segmented lesions are ABCD features, Statistical features and is given to the classifier. The classification is done by Machine Learning Algorithms (FFNN, SVM, KNN). The performance is analysed by the sensitivity, specificity, accuracy, Positive predictive value, negative predictive value and manually by Total Dermatoscopy Score (TDS) for 9 different classification cases. The best among the cases is 96.7% accuracy is for FFNN algorithm.