Bag-of-Features Classification Model for the Diagnose of Melanoma in Dermoscopy Images Using Color and Texture Descriptors

Melanoma detection using medical oriented approaches has been a trend in skin cancer research. This paper uses a Bag-of-Feature model for the detection of melanomas in dermoscopy images and aims at identifying the role of different local texture and color descriptors. This is a medical oriented approach and the reported results are promising (Sensitivity = 93%, Specificity=85%), showing the ability of this method to describe medical dermoscopic features. Moreover, the results show that color descriptors outperform texture ones.

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