• DocumentCode
    2729527
  • Title

    Multinomial Bayesian Kernel Logistic Discriminant Based Method for Skin Detection

  • Author

    Filali, Imen ; Ziou, Djemel ; Benblidia, Nadjia

  • Author_Institution
    Dept. d´´Inf., Univ. Saad Dahlab, Blida, Algeria
  • fYear
    2012
  • fDate
    25-29 Nov. 2012
  • Firstpage
    420
  • Lastpage
    425
  • Abstract
    This paper deals with the detection of skin pixels in color images containing different ethnic groups´ skins. These images are subject to any form of distortion such as the variation of illumination and the variety of capture devices. We have used combination scheme of linear classifiers where each one is devoted to a specific ethnic group. We used kernel Bayesian logistic regression because it outperforms many existing linear classifiers. It is shown that our scheme outperforms some existing skin detection methods that provide high classification scores.
  • Keywords
    Bayes methods; image classification; image colour analysis; regression analysis; capture device; classification scores; color images; ethnic group skins; kernel Bayesian logistic regression; linear classifiers; multinomial Bayesian kernel logistic discriminant; skin detection; skin detection method; skin pixel; Bayesian methods; Covariance matrix; Equations; Image color analysis; Kernel; Mathematical model; Skin; Bayesian estimation; Color skin detection; Kernel Fisher´s discriminant; Logistic regression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Image Technology and Internet Based Systems (SITIS), 2012 Eighth International Conference on
  • Conference_Location
    Naples
  • Print_ISBN
    978-1-4673-5152-2
  • Type

    conf

  • DOI
    10.1109/SITIS.2012.67
  • Filename
    6395125