A Comparative Study of Melanoma Skin Cancer Detection in Traditional and Current Image Processing Techniques

Skin cancer is a major health issue in the present day especially melanoma skin cancer. In general most of the skin cancers are cured if they are detectedin the early stage. With the rapid growth of skin cancer, there is a need for an automated computerized diagnosis mechanism of skin cancer in the early stage is required. Many of the skin cancer images have similar visual characteristics. It is an important challenging task to extract the features from the skin cancer images. The automated computerized diagnosis mechanism helps to improve the accurate analysis of skin diseases which helps the dermatologists to accelerate the diagnostic time and improve the better treatment for the patients. This paper mainly presents the comparative study on traditional image processing and current technologies of different image processing techniques for skin cancer image classification, preprocessing techniques, Feature extraction, and image segmentation datasets.