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Skin cancers are the most common form of cancers in humans. It is a deadly type of cancer affecting skin. Most of the skin cancers are curable at initial stages. So an early detection of skin cancer can save the patients. Conventional diagnosis method for skin cancer detection is Biopsy method. It is done by removing or scraping off skin and that sample undergoes a series of laboratory testing. It is painful and time consuming one. Computer based skin cancer detection is more advantageous to patients, by which patients can identify the skin cancer without going to hospital or without the help of a doctor. Computer based detection uses imaging techniques and Artificial Intelligence. The different stages of detection involves- collection of dermoscopic images, filtering the images for removing hairs and noises, segmenting the images using Maximum Entropy Threshold, feature extraction using Gray Level Co-occurrence Matrix(GLCM), and classification using Artificial Neural Network(ANN). Back-Propagation Neural (BPN) Network is used for classification purpose. It classifies the given data set into cancerous or non-cancerous.
Jaleel et al. (Fri,) studied this question.