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
Link To Document :
بازگشت