Detection of melanoma skin disease by extracting high level features for skin lesions

Melanoma is a very dangerous type of skin cancer as compared to others. It can be cured, when diagnosed in its early stage. The detection and diagnosis of skin cancer is difficult using earlier conventional methods. The accurate detection and diagnosis of melanoma is possible using suitable image processing techniques. High level features, measures asymmetry of skin lesion images. These features can be used to diagnose lesions as skin cancer (melanoma). This paper presents large set of low level features for analysing skin lesions. The best classification is obtained by combining the low level feature set with the high level feature set. The result shows that this method can be used and further developed as a tool for detection and classification of skin cancer (melanoma).