Human Skin Detection Using RGB, HSV and YCbCr Color Models

DOI

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.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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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  - Proceedings of the International Conference on Communication and Signal Processing 2016 (ICCASP 2016)
PB  - Atlantis Press
SP  - 324
EP  - 332
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccasp-16.2017.51
DO  - 10.2991/iccasp-16.2017.51
ID  - Kolkur2016/12
ER  -