Human Skin Detection Using RGB, HSV and YCbCr Color Models
- S. Kolkur, D. Kalbande, P. Shimpi, C. Bapat, J. Jatakia
- Corresponding Author
- S. Kolkur
Available Online December 2016.
- https://doi.org/10.2991/iccasp-16.2017.51How to use a DOI?
- Skin Detection, Color Models, Image Processing, Classifier
- 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.
- 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 -