Open AccessStudy on face detection based on an improved Gaussian skin color model
Author(s) -
Lingli Tan
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1883/1/012017
Subject(s) - artificial intelligence , ycbcr , skin color , face detection , hsl and hsv , gaussian network model , computer science , face (sociological concept) , computer vision , adaboost , gaussian , pattern recognition (psychology) , color image , image (mathematics) , facial recognition system , support vector machine , image processing , physics , medicine , social science , virus , virology , quantum mechanics , sociology
An improved Gaussian skin color model is proposed for face detection applications. It overcomes the issue that the traditional models become ineffective in extracting the skin color region in the presence of diverse skin colors and illuminations. It is a two-dimensional gaussian mixture model based on H-SV (i.e., an improved HSV) and YCbCr color spaces. Experimental results from several face image databases show that the detection accuracy is improved by 35.8% and 6.3%, respectively, compared to a traditional gaussian skin model and Adaboost algorithm.