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Early detection of melanoma skin cancer is crucial for effective treatment. Melanoma is considered the most dangerous form of skin cancer due to its higher likelihood of spreading to other parts of the body if not diagnosed and treated promptly. To address this challenge, non-invasive medical computer vision and medical image processing techniques have become increasingly important in clinical diagnosis of various diseases, including melanoma. These techniques offer automated image analysis tools that enable accurate and rapid evaluation of skin lesions.To assess the severity of the lesions, a total dermo copy score was calculated based on the extracted features. Finally, classification was carried out using a convolutional neural network (CNN) model. The results of the study demonstrated a high classification accuracy of 96.5%, indicating the effectiveness of the proposed approach in accurately identifying melanoma skin cancer.

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