Skin Detection using Histogram depend on the Mean Shift Algorithm
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Skin Detection using Histogram depend on the Mean Shift Algorithm

Authors: Soo- Young Ye, Ki-Gon Nam, Ki-Won Byun

Abstract:

In this paper, we were introduces a skin detection method using a histogram approximation based on the mean shift algorithm. The proposed method applies the mean shift procedure to a histogram of a skin map of the input image, generated by comparison with standard skin colors in the CbCr color space, and divides the background from the skin region by selecting the maximum value according to brightness level. The proposed method detects the skin region using the mean shift procedure to determine a maximum value that becomes the dividing point, rather than using a manually selected threshold value, as in existing techniques. Even when skin color is contaminated by illumination, the procedure can accurately segment the skin region and the background region. The proposed method may be useful in detecting facial regions as a pretreatment for face recognition in various types of illumination.

Keywords: Skin region detection, mean shift, histogram approximation.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1330109

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References:


[1] Z. Jiang, Z. Wu and M. Yao. "Skin Detection on Images with Color Deviation", IEEE Trans Congress on Services, Part Ôàí, pp. 171-174, 2008.
[2] S. Kherchaoui and A. Houacine, "Face Detection Based on A Model of the Skin Color with Constranins and Template Matching", Int'l Conf. Machine and Web Intell. pp. 469-472., 2010
[3] L. Zhengming, Z. Tong and Z. Jin," Skin Detection in Color Images", Int'l Conf. ICCET, pp. 156-159, 2010.
[4] T. Uongqiu, Y. Faling, C. Guohua and J. Shizhong." Skin Color Detection by Illumination Estimation and Normalization in Shadow Regions", IEEE. Conf. ICIA. pp. 1082-1085, 2010.
[5] D.A. Socolinsky, A. Selinger, and J.D. Neuheisel," Face Recognition with Visible and Thermal Infrared Imagery", Computer Vision Image Understanding, vol. 91, no.2, pp. 72-114, 2003.
[6] S.G. Kong, J. Heo, B.R. Abidi, J. Paik, and M.A. Abidi, "Recent Advances in Visual and Infrared Face Recognition: A Review". Computer Vision Image Understanding, vol.97, no.1, pp.103-135, 2005.
[7] A.S. Nunez and M. J Mendenhall," Detection of Human Skin in Near Infrared Hyperspectral Imagery", IEEE. Int'l IGARSS. 2, pp. 621-624, 2008.
[8] C. Liensberger, J. Stottinger and M. Kampel, "Color-Based and Context-Aware Skin Detection for Online Video Annotation", IEEE. Trans. Intl'l MMSP. pp. 1-6, 2009.
[9] Z. Pan, G. Healey, M. Prasad, and B. Tromberg, "Face Recognition in Hyperspectral Images", IEEE Trans. Pattern Anal. Mach. Intell, vol.25, no.12, pp.1552-1559, 2003.
[10] W. Xinyu, X, Huosheng, W. Heng and L. Heng, "Robust Real-Time Face Detection with Skin Color Detection and The Modified Census Transform". Int'l Conf. ICIA. pp. 590-595, 2008.
[11] R. L. Hsu, M. Abdel-Mottaleb, and A. K. Jain. "Face Detection in Color Images", IEEE Trans. on PAMI, vol.24, no.5, pp.696-706, 2002.