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A Novel Skin Tone Detection using Hybrid Approach by New Color Space

by C. Prema, D. Manimegalai
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 46 - Number 7
Year of Publication: 2012
Authors: C. Prema, D. Manimegalai
10.5120/6919-9259

C. Prema, D. Manimegalai . A Novel Skin Tone Detection using Hybrid Approach by New Color Space. International Journal of Computer Applications. 46, 7 ( May 2012), 15-19. DOI=10.5120/6919-9259

@article{ 10.5120/6919-9259,
author = { C. Prema, D. Manimegalai },
title = { A Novel Skin Tone Detection using Hybrid Approach by New Color Space },
journal = { International Journal of Computer Applications },
issue_date = { May 2012 },
volume = { 46 },
number = { 7 },
month = { May },
year = { 2012 },
issn = { 0975-8887 },
pages = { 15-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume46/number7/6919-9259/ },
doi = { 10.5120/6919-9259 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:39:07.830216+05:30
%A C. Prema
%A D. Manimegalai
%T A Novel Skin Tone Detection using Hybrid Approach by New Color Space
%J International Journal of Computer Applications
%@ 0975-8887
%V 46
%N 7
%P 15-19
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Skin is the most widely used primitive in human image processing research and computer vision with application ranging from face detection and person tracking to pornography filtering. It has proven to be a useful and robust cue for detecting human parts in images since (i) it is invariant to orientation and size (ii) it gives extra dimension compared to gray scale methods and (iii) it is fast to process. The main problems with the robustness of skin color detection depend on illumination condition, it varies between individuals, many everyday life objects are skin color like and skin color is not unique. To detect skin tone in images with this complex background, we presented a method based on hybrid approach. In this approach, the Cheddad's approach is combined with Cr of YCbCr color space. In Cheddad's approach, the red channel is discarded. Only green and blue channels are used to find the skin tones. Due to the absence of red channel, this approach is not working properly in images which have poor illumination. To improve the performance, we propose to include the Cr component of YCbCr color space. The experimental results show that the proposed approach is simple and preserve skin color better than the previous methods under various illumination and background conditions.

References
  1. Fleck, M. M. , Forsyth, D. A. , and Bregler, C. (1996). Finding naked people. In European Conference on Computer Vision.
  2. K. Sobottka, I. Pitas, A novel method for automatic face segmentation facial feature extraction and tracking, Signal Process, Image Commun. 12 (1998)263-277
  3. Dai Y. ,and Nakano Y. , Face-Texture model based on SGLD and its application in face detection in a color scene, Pattern Recognition,1996,pp. 1007-1017.
  4. J. Yang, W. Lu, A. Waibel, Skin-color modeling and adaptation, ACCV98, 1998
  5. C. Garcia, G. Tziritas, Face detection using quantized skin color regions merging and wavelet packet analysis, IEEE Trans. Multimedia(1999)264–277.
  6. B. D. Zarit, J. B. Super, F. K. H. Quek, Comparison of five color models in skin pixel classification, CCV99, 1999.
  7. M. J. Jones, J. M. Rehg, Statistical color models with application to skin detection, CVPR99, 1999
  8. J. C. Terrillon, M. N. Shirazi, H. Fukamachi, S. Akamatsu, Comparative performance of different skin chrominance models and chrominance spaces for the automatic detection of human faces in color images, CFGR00, 2000, pp. 54–61
  9. Chai D. , and Bouzerdoum A. ,2000 A Bayesian approach to skin color classification in ycbcr color space. In Proceedings IEEE Region Ten Conference (TENCON'2000), vol. 2, 421–424 .
  10. Sorianzo M. ,Huovinen S. ,Marinkauppi B, and Laaksonen M. ,2000 Skin detection in video under challenging illumination conditions In Proc. 15th International Conference on Pattern Recognition, vol. 1, 839–842.
  11. J. Brand, J. Mason, A comparative assessment of three approaches to pixel level human skin-detection, ICPR01 1 (2000) 1056–1059.
  12. A. Albiol, L. Torres, E. J. Delp, Optimum color spaces for skin detection, ICIP01, 2001.
  13. Shin M. C. ,Chang K. I and Tsap L. V. 2002 Does color space transformation make any difference on skin detection? In IEEE Workshop on Applications of Computer Vision.
  14. R. L. Hsu, M. Abdel-Mottaleb, A. K. Jain, Face detection in color images, IEEE Trans. Pattern Anal. Machine Intell. 24 (5) (2002) 696–706.
  15. G. Gomez, M. Sanchez, L. E. Sucar, On selecting an appropriate colour space for skin detection, Springer-Verlag: Lecture Notes in Artificial Intelligence, vol. 2313, 2002, pp. 70–79.
  16. V. Vezhnevets, V. Sazonov, A. Andreeva, A survey on pixel-based skin color detection techniques,GRAPHICON03, 2003, pp. 85–92.
  17. Son Lam Phung, Douglas Chai Abdesselam Bouzerdoum, Adaptive skin segmentation in color images,IEEE International Conference on Acoustics, speech and signal processing,2003, pp. 353-356.
  18. A. Pietrowcew. Face detection in color images using fuzzy Hough transform , Opto Electronics Review, v. 11(3),(2003),247p.
  19. P. Peer, J. Kovac, F. Solina, Human skin color clustering for face Detection, EUROCON 1993,Ljubljana, Slovenia ,pp 144-148, September 2003
  20. Z. Fu, J. Yang, W. Hu, T. Tan, Mixture clustering using multidimensional histograms for skin detection, ICPR04, 2004, pp. 549–552
  21. S. L. Phung, A. Bouzerdoum, D. Chai, Skin segmentation using color pixel classification: analysis and comparison, IEEE Trans. Pattern Anal. Mach. Intell. 27 (1) (2005).
  22. Soria-Frisch A. ,Verschae R. , and Olano A. ,(2007), Fuzzy fusion for skin detection, Fuzzy Sets and Systems 158:325-336
  23. P. Kakumanu, S. Makrogiannis, N. Bourbakis, A survey on skin color modeling and detection methods, Pattern Recognition 40 (2007)
  24. Handaru Jati, Dhanapal Durai Dominic, Human Skin Detection Using Defined Skin Region, 978-1-4244-2328-6/08© 2008 IEEE.
  25. Abbas Cheddad, Joan Condell, Kevin Curran and Paul Mc Kevitt, A New color space for skin detection 978-1-4244-5654-3/09,ICIP 2009.
  26. Zhang Zhengzhen, Shi Yuexiang, Skin Color Detecting Unite YCgCb Color Space with YCgCr Color Space 978-1-4244-3986-7/09.
  27. Li Zhengming Zhan Tong Zhang Jin, Skin Detection in Color Images,978-1-4244-6349-7/10/©2010IEEE
Index Terms

Computer Science
Information Sciences

Keywords

Color Transformation Cheddad's Approach Ycbcr Color Space Skin Tone Detection

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