Title :
Towards automatic acne detection using a MRF model with chromophore descriptors
Author :
Zhao Liu ; Zerubia, Josiane
Author_Institution :
Ayin Res. Group, INRIA Sophia Antipolis Mediterranee, Sophia Antipolis, France
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.
Keywords :
Markov processes; diseases; face recognition; image segmentation; inspection; medical image processing; MRF model; Markov random field model; RGB acne images; acne detection approach; acne segmentation methods; automatic acne detection; bilateral decomposition; chromophore descriptors; human face; human visual inspection; hyperpigmentation scar; inflammatory response; prevalent skin disease; Abstracts; Biomedical optical imaging; Computational modeling; Image segmentation; Indexes; Labeling; Optical imaging; Markov random fields (MRFs); acne detection; chromophore descriptors; image segmentation;
Conference_Titel :
Signal Processing Conference (EUSIPCO), 2013 Proceedings of the 21st European
Conference_Location :
Marrakech