Human Skin Detection Using RGB, HSV and YCbCr Color Models
August 09, 2017 Β· Declared Dead Β· π Proceedings of the International Conference on Communication and Signal Processing 2016 (ICCASP 2016)
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Authors
S. Kolkur, D. Kalbande, P. Shimpi, C. Bapat, J. Jatakia
arXiv ID
1708.02694
Category
cs.CV: Computer Vision
Cross-listed
q-bio.OT
Citations
215
Venue
Proceedings of the International Conference on Communication and Signal Processing 2016 (ICCASP 2016)
Last Checked
4 months ago
Abstract
Human Skin detection deals with the recognition of skin-colored pixels and regions in a given image. Skin color is often used in human skin detection because it is invariant to orientation and size and is fast to process. A new human skin detection algorithm is proposed in this paper. The three main parameters for recognizing a skin pixel are RGB (Red, Green, Blue), HSV (Hue, Saturation, Value) and YCbCr (Luminance, Chrominance) color models. The objective of proposed algorithm is to improve the recognition of skin pixels in given images. The algorithm not only considers individual ranges of the three color parameters but also takes into ac- count combinational ranges which provide greater accuracy in recognizing the skin area in a given image.
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