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International Journal of Image, Graphics and Signal Processing(IJIGSP)

ISSN: 2074-9074 (Print), ISSN: 2074-9082 (Online)

Published By: MECS Press

IJIGSP Vol.4, No.4, May. 2012

Skin Color Segmentation in YCBCR Color Space with Adaptive Fuzzy Neural Network (Anfis)

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Author(s)

Mohammad Saber Iraji,Azam Tosinia

Index Terms

Skin color segmentation,image processing,fuzzy,anfis,color space

Abstract

In this paper, an efficient and accurate method for human color skin recognition in color images with different light intensity will proposed .first we transform inputted color image from RGB color space to YCBCR color space and then accurate and appropriate decision on that if it is in human color skin or not will be adopted according to YCBCR color space using fuzzy, adaptive fuzzy neural network(anfis) methods for each pixel of that image. In our proposed system adaptive fuzzy neural network(anfis) has less error and system worked more accurate and appropriative than prior methods.

Cite This Paper

Mohammad Saber Iraji,Azam Tosinia,"Skin Color Segmentation in YCBCR Color Space with Adaptive Fuzzy Neural Network (Anfis)",IJIGSP,vol.4,no.4,pp.35-41,2012.

Reference

[1]Lin.Ch ,” Face detection in complicated backgrounds and different llumination conditions by using YCbCr color space and neural network “, National Taipei University, Taipei 10433, Taiwan, ROC,2007

[2]S.Mitra,Y.Hayashi. Neuro-fuzzy rule generation: Survey in soft computing framework. IEEE Transactions on Neural Networks,2000, 11(3), 748–768.

[3]H.R.Berenji, P.Khedkar, P.” Learning and tuning fuzzy logic controllers through reinforcements”. IEEE Transactions on Neural Networks, 1992, 3, 724–740.

[4]Juang.C.F , Shiu. Sh.J , “Using self-organizing fuzzy network with support vector learning for face detection in color image”s ,Department of Electrical Engineering, National Chung-Hsing University, Taichung 402, Taiwan, ROC,2007.

[5]Cheng.W.Y, Juang.Ch.F ,” An incremental support vector machine-trained TS-type fuzzy system for online classification problems” , Department of Electrical Engineering, National Chung-Hsing University, Taichung 402, Taiwan, ROC,2010

[6]Nasrabadi.A,Haddadnia.J,” Skin Color Segm- entation by Fuzzy Filter , International Journal of Computer and Electrical Engineering, Vol.2, No.6, December, 2010,1793-8163

[7]Ibrahim Khan. M , Bhuiyan.A.A ,” Facial Expression Recognition for Human-Robot Interface“, IJCSNS International Journal of Computer Science and Network S ecurity, VOL.9 No.4, April 2009 [8]Sivanandum.S.N,Sumathi.S,Deepa.S.N,“Introduc-tion to Fuzzy Logic Using MATLAB”, Springer-Verlag, Berlin/Heidelberg, 2007.

[9]Poynton.Cha, “Digital Video and HDTV”, Chapter 24, pp. 291–292, Morgan Kaufman, 2003.

[10]Nodaa.H,Niimia.M,”Department of Systems Innovation and Informatics”, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka 820-8502, Japan,2007.

[11]Chaves-González.J,Vega-Rodriguez.M, Gomez-PulÍdo.J,SánchezPérez.JM.,” Detecting skin in face recognition systems: A colour spaces study ”.Digital Signal Processing Volume 20, Issue 3, May 2010, Pages 806-823 

[12]Hsu.R.L,et all,”Face detection in color images”, IEEE Trans. Pattern Anal. Machine Intell. 24 (5), 2002,696–706.

[13]Garcia. C., Tziritas. G,”Face detection using quantized skin color regions merging and wavelet packet analysis”, IEEE Trans. Multimedia1 (3), 1999,264–277.

[14]Sobottka.K,Pitas.I.,” Novel method for automatic face segmentation, facial feature extraction and tracking”,Signal Process. Image Commun. 12, , 1998, 263–281.

[15]Jones.M., Rehg.J.M.,” Statistical Color Models with Application to Skin Detection”, Technical Report Series, Cambridge Research Laboratory,December 1998.

[16]Saber, E., Tekalp, A.M,” Frontal-view face detection and facial feature extraction using color, shape and symmetry based cost functions”. Pattern Recognition Lett. 19, 1998, 669–680.

[17]Menser.B, Brunig.M,”Locating human faces in color images with complex background”. Intelligent Signal Process. Commun. Systems, December 1999,533–536.

[18]Iraji.ms, Eshragh Jahromi.a.h , tosinia.a,” Failure detection and classification of circular sheets through the methods of perceptron neural network, lvq and neurofuzzy “,3rd International Conference on Intelligent and Advanced Systems, Kuala Lumpur, IEEE,2010