21 September 2015 Texture descriptors based on adaptive neighborhoods for classification of pigmented skin lesions
Author Affiliations +
Abstract
Different texture descriptors are proposed for the automatic classification of skin lesions from dermoscopic images. They are based on color texture analysis obtained from (1) color mathematical morphology (MM) and Kohonen self-organizing maps (SOMs) or (2) local binary patterns (LBPs), computed with the use of local adaptive neighborhoods of the image. Neither of these two approaches needs a previous segmentation process. In the first proposed descriptor, the adaptive neighborhoods are used as structuring elements to carry out adaptive MM operations which are further combined by using Kohonen SOM; this has been compared with a nonadaptive version. In the second one, the adaptive neighborhoods enable geometrical feature maps to be defined, from which LBP histograms are computed. This has also been compared with a classical LBP approach. A receiver operating characteristics analysis of the experimental results shows that the adaptive neighborhood-based LBP approach yields the best results. It outperforms the nonadaptive versions of the proposed descriptors and the dermatologists’ visual predictions.
© 2015 SPIE and IS&T
Victor González-Castro, Victor González-Castro, Johan Debayle, Johan Debayle, Yanal Wazaefi, Yanal Wazaefi, Mehdi Rahim, Mehdi Rahim, Caroline Gaudy-Marqueste, Caroline Gaudy-Marqueste, Jean-Jacques Grob, Jean-Jacques Grob, Bernard Fertil, Bernard Fertil, } "Texture descriptors based on adaptive neighborhoods for classification of pigmented skin lesions," Journal of Electronic Imaging 24(6), 061104 (21 September 2015). https://doi.org/10.1117/1.JEI.24.6.061104 . Submission:
JOURNAL ARTICLE
8 PAGES


SHARE
Back to Top