A Simplified Approach for Melanoma Skin Disease Identification

Beauty brings happiness to all humankind; maintaining beauty is the primary task of all human beings in this globe. Skin plays a vital role in beautification. Any Continuous discomfort in the skin may cause skin diseases. Skin Infections may be due to fungus infections, bacterial infections, viral infections, or any allergy. The worst case of these infections may lead to skin cancer. As a result, the utmost care should be taken to diagnose and treat it immediately before spreading it all over the body. The treatment process and the expenditure for the same are a significant threat to the patients. Even a Dermatologist finds a great deal in finding some severe problems in skin diseases. A course of lab tests has to be made to diagnose some severe accusations and their stages of infections in the skin. Owing to this situation nowadays, medical images have made a significant contribution to early diagnosis. An image processing approach with an easily driven Application Programmable Interface commonly known as API, has been proposed to diagnose skin diseases at their earlier stages. The approach inputs the affected skin area's digital image as input, and a series of digital image analyses are applied to identify the type of disease. The image processing follows preprocessing, segmentation, feature extraction, and classification steps, which apply contrast stretching and median filter, Fuzzy C Means, Grey Level Co-Occurrence Matrix(GLCM), and Gabor filter, Support Vector Machine respectively. These methodologies are applied in every phase of the image analysis implemented using MATLAB for its efficiency. This methodology gives a simple approach to detect a skin disease, especially melanoma. This API is expected to be further extended to detect all types of skin diseases in the future to improve its efficiency.