Proceedings of the International Conference on Communication and Signal Processing 2016 (ICCASP 2016)

Human Skin Detection Using RGB, HSV and YCbCr Color Models

Authors
S. Kolkur, D. Kalbande, P. Shimpi, C. Bapat, J. Jatakia
Corresponding Author
S. Kolkur
Available Online December 2016.
DOI
https://doi.org/10.2991/iccasp-16.2017.51How to use a DOI?
Keywords
Skin Detection, Color Models, Image Processing, Classifier
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 account combi-national ranges which provide greater accuracy in recognizing the skin area in a given image.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
International Conference on Communication and Signal Processing 2016 (ICCASP 2016)
Part of series
Advances in Intelligent Systems Research
Publication Date
December 2016
ISBN
978-94-6252-305-0
DOI
https://doi.org/10.2991/iccasp-16.2017.51How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - S. Kolkur
AU  - D. Kalbande
AU  - P. Shimpi
AU  - C. Bapat
AU  - J. Jatakia
PY  - 2016/12
DA  - 2016/12
TI  - Human Skin Detection Using RGB, HSV and YCbCr Color Models
BT  - International Conference on Communication and Signal Processing 2016 (ICCASP 2016)
PB  - Atlantis Press
UR  - https://doi.org/10.2991/iccasp-16.2017.51
DO  - https://doi.org/10.2991/iccasp-16.2017.51
ID  - Kolkur2016/12
ER  -