Skin color constancy for illumination invariant skin segmentation

2005 ◽  
Author(s):  
Rajkiran Gottumukkal ◽  
Vijayan Asari
Keyword(s):  
Skin Color ◽  
Color Constancy ◽  
Illumination Invariant ◽  
Skin Segmentation

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.

A Novel Piece-Wise Linear Algorithm for Human Skin Segmentation

2015 ◽  
Vol 743 ◽  
pp. 317-320
Author(s):  
Ravi Subban ◽  
Pasupathi Perumalsamy ◽  
G. Annalakshmi
Keyword(s):  
Skin Color ◽  
Color Space ◽  
Skin Detection ◽  
Color Spaces ◽  
Color Component ◽  
Skin Segmentation ◽  
Space Transformation ◽  
Color Space Transformation ◽  
Comprehensive Knowledge ◽  
Novel Method

This paper presents a novel method for skin segmentation in color images using piece-wise linear bound skin detection. Various color schemes are investigated and evaluated to find the effect of color space transformation over the skin detection performance. The comprehensive knowledge about the various color spaces helps in skin color modeling evaluation. The absence of the luminance component increases performance, which also supports in finding the appropriate color space for skin detection. The single color component produces the better performance than combined color component and reduces computational complexity.

scholarly journals ADAPTIVE SKIN DETECTION UNDER UNCONSTRAINED LIGHTING CONDITIONS USING A BIGAUSSIAN MODEL AND ILLUMINATION ESTIMATION

2011 ◽  
Vol 24 (1) ◽  
pp. 21 ◽  
Author(s):  
Jian-Hua Zheng ◽  
Chong-Yang Hao ◽  
Yang-Yu Fan ◽  
Xian-Yong Zang
Keyword(s):  
Skin Color ◽  
Gaussian Model ◽  
Classification Performance ◽  
Skin Detection ◽  
Illumination Estimation ◽  
Skin Segmentation ◽  
Detection Model ◽  
Detection Algorithms ◽  
Lighting Conditions ◽  
Combined Models

An algorithm is proposed to improve the performance of skin detection algorithms under poor illumination conditions. A hybrid skin detection model is addressed to solve these problems by combining two Gaussian models of skin under normal conditions and bright illumination. According to the distribution of the combined models, the algorithm automatically evaluates the skin segmentation result of an adaptive threshold algorithm based on a Gaussian model by estimating the illumination conditions of image. If the estimation result shows that the illumination condition is very different from the normal one, the skin color of the original image needs compensation, and then the algorithm feeds the compensated image back to the Gaussian model for finer skin detection. The experimental results show that our algorithm can cope with a complex illumination change and greatly improve skin classification performance under inferior illumination conditions.

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