Abstract
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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Barata, C., Marques, J.S., Mendonça, T. (2013). Bag-of-Features Classification Model for the Diagnose of Melanoma in Dermoscopy Images Using Color and Texture Descriptors. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2013. Lecture Notes in Computer Science, vol 7950. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39094-4_62
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DOI: https://doi.org/10.1007/978-3-642-39094-4_62
Publisher Name: Springer, Berlin, Heidelberg
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