Published Paper Details:

Skin is an extra ordinary human structure. There are various types of skin cancer. And people are unaware about it. There are large number of skin diseases and some of them are most common. Due to lack of medical facilities available In remote areas, patients usually ignore it. The diagnose of this skin cancer also take the longer time. Melanoma skin cancer detection at an early stage is crucial for an efficient treatment. Recently, it is well known that, the most dangerous form of skin cancer among the other types of skin cancer is melanoma because it's much more likely to spread to other parts of the body if not diagnosed and treated early. The non- invasive medical computer vision or medical image processing plays increasingly significant role in clinical diagnosis of different diseases. Such techniques provide an automatic image analysis tool for an accurate and fast evaluation of the lesion. The steps involved in this study are collecting Dermoscopy image database, preprocessing, segmentation using thresholding, statistical feature extraction using Gray Level Co-occurrence Matrix (GLCM), Asymmetry, Border, Color, Diameter, (ABCD) etc., feature selection using Principal component analysis (PCA), calculating total Dermoscopy Score and then classification using Convocation neural network (CNN After using the publicly accessible data set, an accuracy of 89.5 percent and a training accuracy of 93.7 percent were reached..