Detection of Skin Cancer Based on Image Processing using Machine Learning

Abstract

Early recognition of malignant melanoma is critical for effective therapy. Melanoma, of the many basal cell carcinomas, is now widely known as the most harmful because it will spread to the parts of the body if it is not identified and given treatment in early stage. Medical computer vision or medical image processing, which is non-invasive, is becoming increasingly important in the clinical diagnosis of many disorders. Melanoma diagnosis is done using both clinical and automated methods. Early detection of malignant melanoma has a lot of potential using image-based computer-aided diagnosis methods. Automatically identifying the type of skin cancer from photos can help with quick diagnosis and increased accuracy, saving time. Using machine learning and image processing techniques, this project will detect and classify types of skin cancer. Dermoscopic images are used as feed in the pre-processing step.