Improvement of Non-frontal Face Skin Color Model Based on YCgCr Color Space

In non-frontal situations, the image generally does not contain complete facial information, and skin color is the most important feature for detecting human faces. In order to improve the detection effect of non-frontal face skin color and applicable scenarios, this paper first analyzes and compare...

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Bibliographic Details
Published in2021 40th Chinese Control Conference (CCC) pp. 7218 - 7222
Main Authors Sun, Yigang, Shen, Tianfei, Xu, Zhengqi
Format Conference Proceeding
LanguageEnglish
Published Technical Committee on Control Theory, Chinese Association of Automation 26.07.2021
Subjects
Analytical models
Brightness
ellipse model
Feature extraction
Gaussian skin tone model
Image color analysis
Image segmentation
Lighting
non-frontal face
Otsu
Skin
YCgCr
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Summary:In non-frontal situations, the image generally does not contain complete facial information, and skin color is the most important feature for detecting human faces. In order to improve the detection effect of non-frontal face skin color and applicable scenarios, this paper first analyzes and compares the YCbCr and YCgCr color spaces. Then, by comparing the fixed threshold method, the Gaussian skin color model method and the Otsu method, it is found that the Gaussian skin color model method is the most effective method, but still needs improvement. This paper proposes the Otsu method to optimize the threshold calculation in the Gaussian skin model, and the nonlinear segmented ellipse model reduces the impact of brightness. Experimental results show that this method can eliminate skin-like backgrounds more effectively, and can still maintain a better detection rate under dim lighting, and has a more ideal detection effect.
ISSN:2161-2927
DOI:10.23919/CCC52363.2021.9549467