Description

Skin cancers are cancers that arise from the skin. They are due to the development of abnormal cells that have the ability to invade or spread to other parts of the body. There are three main types: basal-cell cancer (BCC), squamous-cell cancer (SCC) and melanoma. Melanoma is a type of cancer that develops from the pigment-containing cells known as melanocytes. Melanomas typically occur in the skin but may rarely occur in the mouth, intestines, or eye. Identification of skin cancer can be done based on the Melanoma images. The melanoma images were enhanced based on four types of enhancement methods. The enhancement process highlights the affected portion in the images and hence they can be easily identified. The features were extracted from the images based on the affine detectors. The extracted features were then classified in order to identify the defected portions of the images. The performance of the process is measured. The main objective of the process is to segment the tumorous portions in the melanoma images. And to enhance the images based on color constancy methods. To divide the images into patches and extract the features from the images based on the affine features extracted from the images. To classify the tumorous and non-tumorous portions in the images based on SVM classifier.