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Proceedings Paper

An algorithm for the characterization of digital images of pigmented lesions of human skin
Author(s): Laura Y. Mera-González; José A. Delgado-Atencio; Juan C. Valdiviezo-Navarro; Margarita Cunill-Rodríguez
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Paper Abstract

Melanoma is the most deadly form of skin cancer in human in all over the world with an increase number of victims yearly. One traditional form of diagnosis melanoma is by using the so called ABCDE rule which stands for Asymmetry, Border, Color, Diameter and Evolution of the lesion. For melanoma lesions, the color as a descriptor exhibits heterogeneous values, ranging from light brown to dark brown (sometimes blue reddish or even white). Therefore, investigating on color features from digital melanoma images could provide insights for developing automated algorithms for melanoma discrimination from common nevus. In this research work, an algorithm is proposed and tested to characterize the color in a pigmented lesion. The developed algorithm measures the hue of different sites in the same pigmented area from a digital image using the HSI color space. The algorithm was applied to 40 digital images of unequivocal melanomas and 40 images of common nevus, which were taken from several data bases. Preliminary results indicate that visible color changes of melanoma sites are well accounted by the proposed algorithm. Other factors, such as quality of images and the influence of the shiny areas on the results obtained with the proposed algorithm are discussed.

Paper Details

Date Published: 23 September 2014
PDF: 8 pages
Proc. SPIE 9217, Applications of Digital Image Processing XXXVII, 921718 (23 September 2014); doi: 10.1117/12.2062425
Show Author Affiliations
Laura Y. Mera-González, Univ. Politécnica de Tulancingo (Mexico)
José A. Delgado-Atencio, Univ. Politécnica de Tulancingo (Mexico)
Juan C. Valdiviezo-Navarro, Univ. Politécnica de Tulancingo (Mexico)
Margarita Cunill-Rodríguez, Univ. Politécnica de Tulancingo (Mexico)

Published in SPIE Proceedings Vol. 9217:
Applications of Digital Image Processing XXXVII
Andrew G. Tescher, Editor(s)

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