Automatic Classification of Skin Cancer Using KNN, SVM and CNN
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Publication date: 2017-02-20
Eurasian J Anal Chem 2017;12(1):133–138
A skin cancer classification system has been designed and developed. This work presents a new approach to the automated classification of skin cancer images based on texture and colour features. To remove the unwanted noises in the skin image, median filtering is used. In the next stage gray level co-occurrence matrix and colour features are extracted. Finally, k-nearest neighbour, support vector machine and convolutional neural networks are used to classify the skin cancer images. The application of the proposed method for tracking skin cancer is demonstrated to help pathologists distinguish its type of skin cancer. A classification with an accuracy of 85%, 96% and 98% has been obtained by, k-nearest neighbour support vector machine and convolutional neural networks.