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A Context-aware Approach for Detecting Skin Colored Pixels in Images

by Chandra Mani Sharma, Saurabh Saxena
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 71 - Number 17
Year of Publication: 2013
Authors: Chandra Mani Sharma, Saurabh Saxena
10.5120/12448-9146

Chandra Mani Sharma, Saurabh Saxena . A Context-aware Approach for Detecting Skin Colored Pixels in Images. International Journal of Computer Applications. 71, 17 ( June 2013), 8-13. DOI=10.5120/12448-9146

@article{ 10.5120/12448-9146,
author = { Chandra Mani Sharma, Saurabh Saxena },
title = { A Context-aware Approach for Detecting Skin Colored Pixels in Images },
journal = { International Journal of Computer Applications },
issue_date = { June 2013 },
volume = { 71 },
number = { 17 },
month = { June },
year = { 2013 },
issn = { 0975-8887 },
pages = { 8-13 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume71/number17/12448-9146/ },
doi = { 10.5120/12448-9146 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:35:49.040597+05:30
%A Chandra Mani Sharma
%A Saurabh Saxena
%T A Context-aware Approach for Detecting Skin Colored Pixels in Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 71
%N 17
%P 8-13
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Detecting the human skin and its analysis has number of important applications. This is a challenging task as. in images, the skin color is quite sensitive to the chrominance and intensity of the pixels. So the techniques with a single model for skin fail to cope up with the variation in skin colors because of ethnicity, age, lighting etc. This paper proposes a novel technique for skin detection in color images. The proposed technique has two steps; (i) first the faces of humans are detected in the color images (ii) then based on the statistics captured from the sampling of the face area, the rest of the skin is detected. For face detection purpose, we train a binary classifier using machine learning approach. After face detection, the sampled pixels are matched to find the other exposed skin areas using an approach based on Gaussian model for skin.

References
  1. Wei Ren Tan; Chee Seng Chan; Yogarajah, P. ; Condell, J. , "A Fusion Approach for Efficient Human Skin Detection," IEEE Trans. On Industrial Informatics, Vol. 8, Issue 1, pp. 138-147, 2012.
  2. Xiaojin Zhao; Boussaid, F. ; Bermak, A. ," Characterization of a 0. 18 ? m CMOS Color Processing Scheme for Skin Detection," IEEE Sensors Journal, Vol. 7, Issue 11, pp. 1471-1474, 2007.
  3. Zafarifar, B. ; van den Kerkhof, T. ; de With, P. H. N. "Texture-adaptive skin detection for TV and its real-time implementation on DSP and FPGA," IEEE Trans. On Consumer Electronics, Vol. 58, Issue 1, pp. 161-169, 2012.
  4. Hyun-Chul Do; Ju-Yeon You; Sung-Il Chien, "Skin Color Detection through Estimation and Conversion of Illuminant Color Under Various Illumination," IEEE Trans. On Consumer Electronics, Vol. 53, Issue 3, pp. 1103-1108, 2007.
  5. Fleck, M. M. , Forsyth, D. A. , Bregler, C. : Finding naked people. In: Proceedings of the European Conference on Computer Vision (ECCV). Pp. 593-602, 1996.
  6. Abdel-Mottaleb, M. , Elgammal, A. : Face detection in complex environments from color lmages. In: Proceedings of the International Conference on Image Processing (ICIP), pp. 622-626, 1996.
  7. Senior, A. , Hsu, R. L. , Mottaleb, M. A. , Jain, A. K. : Face detection in color images. IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI), Vol. 24, No. 5, pp. 696-706, 2002.
  8. Imagawa, K. , Lu, S. , Igi, S. : Color-based hands tracking system for sign language recognition. In: FG '98: Proceedings of the 3rd. International Conference on Face & Gesture Recognition, Washington, DC, USA, IEEE Computer Society (1998) 462
  9. Zheng, Q. F. , Zhang, M. J. , Wang, W. Q. : A hybrid approach to detect adult web images. In: PCM (2), pp. 609-616, 2004.
  10. Burger, W. , Burge, M. : Digital Image Processing, an Algorithmic Introduction Using Java. Springer (2008)
  11. Shin, M. C. , Chang, K. I. , Tsap, L. V. : Does colorspace transformation make any difference on skin detection? In: WACV '02: Proceedings of the Sixth IEEEWorkshop on Applications of Computer Vision, Washington, DC, USA, IEEE Computer Society (2002) 275
  12. Albiol, A. , Torres, L. , Delp, E. : Optimum color spaces for skin detection. In: Proceedings of the International Conference on Image Processing (ICIP), pp. 122-124, 2001.
  13. C. M. Sharma, A. K. S. Kushwaha, R. Roshan, R. Porwal, A. Khare,"Intelligent Object Classification Scheme using Machine Learning and Offline Feature Based Technique," Int. J. Computer Science Issues, Vol. 9, Issue 1, No. 3, pp. ,247-256, 2012.
  14. J. Zhu, H. Zou, S. Rosset, and T. Hastie, " Multiclass adaboost, " Int. J. of Statistics and Its Interface, vol. 2, pp. 349-360, 2009.
  15. P. Viola and M. Jones, " Robust real-time object detection," Int. J. of Computer Vision, vol. 57, no. 2, pp. 137–154, 2001.
Index Terms

Computer Science
Information Sciences

Keywords

Skin Detection Image Processing Gaussian Models Face Recognition Multimedia

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