@InProceedings{KuiaskiVieiBorbGamb:2009:StEfIl,
               author = "Kuiaski, Diogo and Vieira Neto, Hugo and Borba, Gustavo and Gamba, 
                         Humberto",
          affiliation = "Post-graduation Program in Electrical Engineering and Industrial 
                         Informatics, Federal University of Techology - Paran{\'a} and 
                         Post-graduation Program in Electrical Engineering and Industrial 
                         Informatics, Federal University of Techology - Paran{\'a} and 
                         Post-graduation Program in Electrical Engineering and Industrial 
                         Informatics, Federal University of Techology - Paran{\'a} and 
                         Post-graduation Program in Electrical Engineering and Industrial 
                         Informatics, Federal University of Techology - Paran{\'a}",
                title = "A Study of the Effect of Illumination Conditions and Color Spaces 
                         on Skin Segmentation",
            booktitle = "Proceedings...",
                 year = "2009",
               editor = "Nonato, Luis Gustavo and Scharcanski, Jacob",
         organization = "Brazilian Symposium on Computer Graphics and Image Processing, 22. 
                         (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "skin segmentation, Bayes theory, image processing, color spaces.",
             abstract = "This work aims at investigating the influence of luminance 
                         information and environment illumination on skin classification. 
                         We explore Bayesian approaches to perform automatic classification 
                         of human skin pixels on digital images, using color features as 
                         input. Two probabilistic skin color models were built on different 
                         color spaces (RGB, normalized RG, HSI, HS, YCbCr and CbCr) and 
                         tested in a task of automatic pixel classification into skin and 
                         non-skin. Analyses of classification performance were done by 
                         presenting an illumination controlled image database containing 
                         images acquired in four different illumination conditions (shadow, 
                         sun, incandescent and fluorescent lights) to these classifiers. 
                         Our experiments show that building probabilistic skin color models 
                         using the CbCr color space generally improves performance of the 
                         classifiers and that best performance is achieved in shadow 
                         illumination.",
  conference-location = "Rio de Janeiro, RJ, Brazil",
      conference-year = "11-14 Oct. 2009",
                  doi = "10.1109/SIBGRAPI.2009.47",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI.2009.47",
             language = "en",
                  ibi = "8JMKD3MGPBW4/35S966P",
                  url = "http://urlib.net/ibi/8JMKD3MGPBW4/35S966P",
           targetfile = "PID950646.pdf",
        urlaccessdate = "2024, Apr. 29"
}