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Reseach Article

An Analysis of Skin Pixel Detection using Different Skin Color Extraction Techniques

by Gururaj P. Surampalli, Dayanand J, Dhananjay M
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 54 - Number 17
Year of Publication: 2012
Authors: Gururaj P. Surampalli, Dayanand J, Dhananjay M
10.5120/8655-2385

Gururaj P. Surampalli, Dayanand J, Dhananjay M . An Analysis of Skin Pixel Detection using Different Skin Color Extraction Techniques. International Journal of Computer Applications. 54, 17 ( September 2012), 1-5. DOI=10.5120/8655-2385

@article{ 10.5120/8655-2385,
author = { Gururaj P. Surampalli, Dayanand J, Dhananjay M },
title = { An Analysis of Skin Pixel Detection using Different Skin Color Extraction Techniques },
journal = { International Journal of Computer Applications },
issue_date = { September 2012 },
volume = { 54 },
number = { 17 },
month = { September },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume54/number17/8655-2385/ },
doi = { 10.5120/8655-2385 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:55:54.499942+05:30
%A Gururaj P. Surampalli
%A Dayanand J
%A Dhananjay M
%T An Analysis of Skin Pixel Detection using Different Skin Color Extraction Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 54
%N 17
%P 1-5
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Automated skin detection from a captured natural image has wide range of application. Detection of skin area in a given image is done through marking skin and non skin pixels. Process of identification of skin pixel is closely associated with color space being used. To select suitable method to extract skin region has motivated this paper. We are using multiple color spaces in a paper to analyze and compare them. We have the different set of images to compare color space. The results indicate that YCbCr provide better performance compare to other color space.

References
  1. E Angelopoulou. Understanding the color of human skin. In Proc. SPIE Conf. On Human Vision and Electronic Imaging VI (SPIE), 4299:243–251, 2001.
  2. J Brand, S Mason, M Roach, and M Pawlewski. Enhancing face detection in colour images using a skin probability map. Int. Conf. on Intelligent Multimedia, Video and Speech Processing, pages 344–347, 2001.
  3. Cynthia A Brewer. Color use guidelines for data representation. Alexandria: American Statistical Association, pages 55–56, 1999.
  4. D N Chandrappa, M Ravishankar, and D R RameshBabu. Automated detection and recognition of face in a crowded scene. International Journal of Computer and Network Security, 2(6):65–70, June 2010.
  5. D N Chandrappa, M Ravishankar, and D R RameshBabu. Face detection in color images using skin color model algorithm based on skin color information. IEEE, pages 254– 258, 2010.
  6. Tarek Abd El-Hafeez. A new system for extracting and detecting skin color regions from pdf documents. International Journal on Computer Science and Engineering( IJCSE), 2(9):2838–2846, 2010.
  7. B Hajar, E Sanaa, J Abdelilah, and A Driss. Recognition of adult video by combining skin detection features with motion information. IEEE, 2010.
  8. Jiang Qiang-rong and Li Hua-lan. Robust human face detection in complicated color images. IEEE Trans, 2010.
  9. S Sanjay, D S Chauhan, V Mayank, and S Richa. A robust skin color based face detection algorithm. Tamkang Journal of Science and Engineering, 6(4):227–234, 2003.
  10. M R Tabassum, A U Gias, M M Kamal, H M Muctadir, M Ibrahim, A K Shakir, A Imran, S Islam, M G Rabbani, S M Khaled, M S Islam, and Z Begum. Comparative study of statistical skin detection algorithms for sub-continental human images. Institute of Information Technology, University of Dhaka, pages 1–8.
  11. Randazzo Vincenzo and Usai Lisa. An improvement of adaboost for face-detection with motion and color information. IEEE 14th International Conference on Image Analysis and Processing (ICIAP), 2007.
  12. Yan-Wen Wu and Xue-Yi Ai. Face detection in color images using adaboost algorithm based on skin color information. IEEE computer society, 2008.
Index Terms

Computer Science
Information Sciences

Keywords

Skin pixel detection Log opponent HSV YIQ YCbCr