Home   >   CSC-OpenAccess Library   >    Manuscript Information
Color Constancy For Improving Skin Detection
Ali Nadian-Ghomsheh
Pages - 479 - 496     |    Revised - 01-12-2014     |    Published - 31-12-2014
Volume - 8   Issue - 6    |    Publication Date - November / December 2014  Table of Contents
Skin Detection, Color Constancy, Gaussian Distribution, White Patch Retinex, Grey World Assumption.
Skin detection is a preliminary step in many human related recognition systems. Most skin detection systems suffer from high false detection rate, resulting from low variance between the skin and non-skin color distributions. This paper proposes the use of simple color correction algorithms with low computation complexity to obtain a corrected version of the skin color distribution, which could lead to more accurate skin detection. White patch retinex, Grey world assumption and several improved versions of these two state of the art correction algorithms were chosen and applied to an image set of 4000. The results, compared with skin detection with no color correction revealed that color correction will improve the skin detection accuracy.
1 Google Scholar 
2 CiteSeerX 
3 refSeek 
4 Scribd 
5 SlideShare 
6 PdfSR 
Al Tairi, Z.H. and M.I. Saripan, Skin segmentation using YUV and RGB color spaces. Journal of information processing systems, 2014. 10(2): p. 283-299.
Berbar, M.A., Skin colour correction and faces detection techniques based on HSL and R colour components. International Journal of Signal and Imaging Systems Engineering, 2014. 7(2): p. 104-115.
Bergasa, L.M., et al., Unsupervised and adaptive Gaussian skin-color model. Image and Vision Computing, 2000. 18(12): p. 987-1003.
Cao, X.Y. and H.F. Liu, A skin detection algorithm based on Bayes decision in the YCbCr color space. Applied Mechanics and Materials, 2012. 121: p. 672-676.
Cheddad, A., et al., A skin tone detection algorithm for an adaptive approach to steganography. Signal Processing, 2009. 89(12): p. 2465-2478.
Cho, K.-M., J.-H. Jang, and K.-S. Hong, Adaptive skin-color filter. Pattern Recognition, 2001. 34(5): p. 1067-1073.
Choi, W., C. Pantofaru, and S. Savarese, A general framework for tracking multiple people from a moving camera. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 2013. 35(7): p. 1577-1591.
Do, H.-C., J.-Y. You, and S.-I. Chien, Skin color detection through estimation and conversion of illuminant color under various illuminations. Consumer Electronics, IEEE Transactions on, 2007. 53(3): p. 1103-1108.
Ebner, M. and J. Hansen, Depth map color constancy. Bio-Algorithms and Med-Systems, 2013. 9(4): p. 167-177.
Ebner, M., Color constancy. Vol. 6. 2007: John Wiley & Sons.
Gijsenij, A., T. Gevers, and J. Van De Weijer, Generalized gamut mapping using image derivative structures for color constancy. International Journal of Computer Vision, 2010. 86(2-3): p. 127-139.
Hammami, M., Y. Chahir, and L. Chen, Webguard: A web filtering engine combining textual, structural, and visual content-based analysis. Knowledge and Data Engineering, IEEE Transactions on, 2006. 18(2): p. 272-284.
Hu, W., et al., Recognition of pornographic web pages by classifying texts and images. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 2007. 29(6): p. 1019-1034.
Jang, S.-W., et al., An adult image identification system based on robust skin segmentation. Journal of Imaging Science and Technology, 2011. 55(2): p. 20508-1.
Jedynak, B., H. Zheng, and M. Daoudi. Statistical models for skin detection. in Computer Vision and Pattern Recognition Workshop, 2003. CVPRW'03. Conference on. 2003. IEEE.
Jobson, D.J., Z.-U. Rahman, and G.A. Woodell, A multiscale retinex for bridging the gap between color images and the human observation of scenes. Image Processing, IEEE Transactions on, 1997. 6(7): p. 965-976.
Jobson, D.J., Z.-U. Rahman, and G.A. Woodell, Properties and performance of a center/surround retinex. Image Processing, IEEE Transactions on, 1997. 6(3): p. 451-462.
Jones, M.J. and J.M. Rehg, Statistical color models with application to skin detection. International Journal of Computer Vision, 2002. 46(1): p. 81-96.
Kakumanu, P., S. Makrogiannis, and N. Bourbakis, A survey of skin-color modeling and detection methods. Pattern recognition, 2007. 40(3): p. 1106-1122.
Kawulok, M., J. Kawulok, and J. Nalepa, Spatial-based skin detection using discriminative skin-presence features. Pattern Recognition Letters, 2014. 41: p. 3-13.
Lee, J.-S., et al., Naked image detection based on adaptive and extensible skin color model. Pattern recognition, 2007. 40(8): p. 2261-2270.
Mohammed, K., B.C. Ennehar, and T. Yamina, Skin detection using gaussian mixture models in YCbCr and HSV color space. Global Journal on Technology, 2012. 1.
Nadian, A. and A. Talebpour, A New Skin Detection Approach for Adult Image Identification. Research Journal of Applied Sciences, Engineering and Technology, 2012. 4(21): p. 4535- 4545.
Nadian, A. and A. Talebpour. Pixel-based skin detection using sinc function. in Computers & Informatics (ISCI), 2011 IEEE Symposium on. 2011. IEEE.
Nadian, A., A. Talebpour, and M. Basseri. Regional skin detection based on eliminating skin- like lambertian surfaces. in Computers & Informatics (ISCI), 2011 IEEE Symposium on. 2011. IEEE.
OJO, J.A. and S.A. Adeniran, Colour face image database for skin segmentation, face detection, recognition and tracking of Black faces under real-life situations. International Journal of Image Processing (IJIP), 2011. 4(6): p. 600.
Rahman, Z.-u., D.J. Jobson, and G.A. Woodell. Resiliency of the multiscale retinex image enhancement algorithm. in Color and Imaging Conference. 1998. Society for Imaging Science and Technology.
Shejul, A.A. and U.L. Kulkarni, A secure skin tone based steganography using wavelet transform. International Journal of computer theory and Engineering, 2011. 3(1): p. 16-22.
Shih, J.-L., C.-H. Lee, and C.-S. Yang, An adult image identification system employing image retrieval technique. Pattern Recognition Letters, 2007. 28(16): p. 2367-2374.
Shoyaib, M., et al., Skin detection using statistics of small amount of training data. Electronics letters, 2012. 48(2): p. 87-88.
Soriano, M., et al., Adaptive skin color modeling using the skin locus for selecting training pixels. Pattern Recognition, 2003. 36(3): p. 681-690.
Sun, H.-M., Skin detection for single images using dynamic skin color modeling. Pattern recognition, 2010. 43(4): p. 1413-1420.
Tao, L., et al. A circuit of configurable skin tone adjusting method base on exact skin color region detection. in Electron Devices and Solid-State Circuits (EDSSC), 2011 International Conference of. 2011. IEEE.
Vezhnevets, V., V. Sazonov, and A. Andreeva. A survey on pixel-based skin color detection techniques. in Proc. Graphicon. 2003. Moscow, Russia.
Wang, Y. and B. Yuan, A novel approach for human face detection from color images under complex background. Pattern Recognition, 2001. 34(10): p. 1983-1992.
Yang, M.-H. and N. Ahuja. Gaussian mixture model for human skin color and its application in image and video databases. in Proc. SPIE: Storage and Retrieval for Image and Video Databases VII. 1999.
Mr. Ali Nadian-Ghomsheh
Cyberspace research group, Shahid Beheshti University, GC Tehran, 1983963113 - Iran

View all special issues >>