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http://dx.doi.org/10.5369/JSST.2012.21.1.28

Human Hand Detection Using Color Vision  

Kim, Jun-Yup (School of Electronic and Electrical Engineering, Daegu University)
Do, Yong-Tae (School of Electronic and Electrical Engineering, Daegu University)
Publication Information
Journal of Sensor Science and Technology / v.21, no.1, 2012 , pp. 28-33 More about this Journal
Abstract
The visual sensing of human hands plays an important part in many man-machine interaction/interface systems. Most existing visionbased hand detection techniques depend on the color cues of human skin. The RGB color image from a vision sensor is often transformed to another color space as a preprocessing of hand detection because the color space transformation is assumed to increase the detection accuracy. However, the actual effect of color space transformation has not been well investigated in literature. This paper discusses a comparative evaluation of the pixel classification performance of hand skin detection in four widely used color spaces; RGB, YIQ, HSV, and normalized rgb. The experimental results indicate that using the normalized red-green color values is the most reliable under different backgrounds, lighting conditions, individuals, and hand postures. The nonlinear classification of pixel colors by the use of a multilayer neural network is also proposed to improve the detection accuracy.
Keywords
Vision Sensing; Color Space; Hand Detection; Human Machine Interaction(HMI); Neural Networks;
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