Towards Automatic Acne Detection Using a MRF Model with Chromophore Descriptors

Zhao Liu 1, * Josiane Zerubia 1
* Auteur correspondant
Abstract : This paper proposes a new acne detection approach using a Markov random field (MRF) model and chromophore descriptors extracted by bilateral decomposition. Compared to most existing acne segmentation methods, the proposed algorithm enables to cope with large-dynamic-range intensity usually existing in conventional RGB acne images captured under uncontrolled environment. Algorithm performance has been tested on acne images of human face from a free public database. Experimental results show that acne segmentation derived from this new approach highly agrees to human visual inspection. Moreover, inflammatory response and hyperpigmentation scar can be well discriminated. It is expected that a computer-assisted diagnostic system for acne severity evaluation will be constructed as a consequence of the present work.
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Communication dans un congrès
European Signal Processing Conference (EUSIPCO), Sep 2013, Marrakech, Morocco. IEEE, 2013
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Dernière modification le : samedi 27 janvier 2018 - 01:31:40
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Zhao Liu, Josiane Zerubia. Towards Automatic Acne Detection Using a MRF Model with Chromophore Descriptors. European Signal Processing Conference (EUSIPCO), Sep 2013, Marrakech, Morocco. IEEE, 2013. 〈hal-00863046〉

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