Face Localization in Color Images Based on Skin Color and Eye Gradient

2011 ◽  
Vol 268-270 ◽  
pp. 1382-1385
Author(s):  
Yun Juan Liang ◽  
Xiao Ying Wu ◽  
Li Juan Ma ◽  
Li Jun Zhang
Keyword(s):  
Skin Color ◽  
Color Images ◽  
Color Model ◽  
Human Face ◽  
Color Information ◽  
Eye Localization ◽  
Illumination Changes ◽  
Skin Color Model ◽  
Candidate Regions ◽  
Face Localization

In color images, skin color is the important information on human face. This paper proposes a method to detect and locate human face rapidly based on skin color information and eye gradient. First, normalized RGB space is converted to HSV space; Secondly, the images are pretreated by smoothing and light compensation to overcome the uneven illumination changes, and then the defined skin color model is used to determine candidate regions of the human face, finally the human face is located accurately through eye localization based on gradient template. Experiments show that the method is fast and effective.

scholarly journals Human Face Detection in Color Images

2021 ◽  
Author(s):  
Jun Gao
Keyword(s):  
Face Detection ◽  
Skin Color ◽  
Video Retrieval ◽  
Color Images ◽  
Human Face ◽  
Detection Scheme ◽  
Retrieval Systems ◽  
Human Face Detection ◽  
The Face ◽  
Video Retrieval Systems

Detection of human face has many realistic and important applications such as human and computer interface, face recognition, face image database management, security access control systems and content-based indexing video retrieval systems. In this report a face detection scheme will be presented. The scheme is designed to operate on color images. In the first stage of algorithm, the skin color regions are detected based on the chrominance information. A color segmentation stage is then employed to make skin color regions to be divided into smaller regions which have homogenous color. Then, we use the iterative luminance segmentation to further separate the detected skin region from other skin-colored objects such as hair, clothes, and wood, based on the high variance of the luminance component in the neighborhood of edges of objects. Post-processing is applied to determine whether skin color regions fit the face constrains on density of skin, size, shape and symmetry and contain the facial features such as eyes and mouths. Experimental results show that the algorithm is robust and is capable of detecting multiple faces in the presence of a complex background which contains the color similar to the skin tone.

An Improved Adaptive Threshold Skin Color Model

2014 ◽  
Vol 610 ◽  
pp. 358-361
Author(s):  
Hong Wei Di ◽  
Wei Xu
Keyword(s):  
Skin Color ◽  
Adaptive Threshold ◽  
Experimental Results ◽  
Color Model ◽  
Threshold Segmentation ◽  
Change Rate ◽  
Skin Segmentation ◽  
Strong Robustness ◽  
Skin Color Model ◽  
Optimum Threshold

To solve the problem that traditional threshold segmentation model is not very robust in skin segmentation under different skin colors and different illuminations, an improved adaptive skin color model is proposed. This model detects the change rate of the skin color pixels by modifying the certain threshold while fixing others, then selects the optimum threshold adaptively. The experimental results show that this algorithm can effectively distinguish skin color regions and background regions, and has strong robustness on light disturbance.

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