A method to detect potentially malignant skin lesions through image segmentation

Melanoma is a form of skin cancer responsible for most cancer deaths. The detection of melanoma in an early stage is still a challenge with high importance. The aim of this paper was the design of a system to analyse the mole’s characteristics, based on the ABCDE criteria, for identifying potentially malignant skin lesions. The segmentation was based on Otzu thresholding, chain code and skeletonization methods were used to compute the main features: asymmetry, border, color and texture, for a future classification of skin lesions as normal or potentially malignant melanoma. The system was evaluated successfully using 92 images with 27 benign and 65 malignant melanomas from Dermatology Information System (DermIS).