Face Recognition Using Chain Codes

Nazmeen B. Boodoo-Jahangeer, Sunilduth Baichoo

Department of Computer Science, University of Mauritius, Reduit, Mauritius..

DOI: 10.4236/jsip.2013.43B027                

Abstract

Face recognition is an active area of biometrics. This study investigates the use of Chain Codes as features for recognition purpose. Firstly a segmentation method, based on skin color model was applied, followed by contour detection, then the chain codes of the contours were determined. The first difference of chain codes were calculated since the latter is invariant to rotation. The features were calculated and stored in a matrix. Experiments were performed using the University of Essex Face database, and results show a recognition rate of 95% with this method, when compared with Principal Components Analysis (PCA) giving 87.5% recognition rate.

Keywords

Face Recognition; Biometrics; Chain Codes; PCA

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	W. W., Bledsoe, “The Model Method in Facial Recognition,” Technical Report, PRI 15, Panoramic Research, Inc., Palo Alto, California, 1964.
[2]	W. Zhao, R. Chellappa, J. Phillips and A. Rosenfeld, “Face Recognition in Still and Video Images: A Literature Survey,” ACM Computing Surveys, Vol. 35, 2003, pp. 399-458. doi;10.1145/954339.954342
[3]	M. Seul, O. Lawrence and M. J., Sammon, “Practical Algorithms for Image Analysis: Description,” Examples and Code, edisi kebrp. USA: Cambridge University Press, 2000.
[4]	A. McAndrew, “Introduction to Digital Image Processing with Matlab,” USA: Thomson Course Technology: pp. 353, 2004.
[5]	C. Jiang, Y. Zhao, W. Xu and X. Meng, “Research of Fingerprint Recognition,” 2009 Eighth IEEE International Conference on Dependable, Autonomic and Secure Computing, 2009, pp. 847-848. doi:10.1109/DASC.2009.102
[6]	P. Kakumanu, S. Makrogiannis and N. Bourbakis, "A Survey of Skin-ColorModeling and Detection Methods", Pattern Recognition 40, 2007, pp 1106- 1122. doi:10.1016/j.patcog.2006.06.010
[7]	V. Vezhnevets, V. Sazonov and A. Andreeva, “A Survey on Pixelbased Skin Color Detection Techniques,” In GraphiCon, Moscow, Russia, 2003.
[8]	R. Gonzalez and E. Woods, Digital Image Processing, 2nd edition, Prentice Hall, 2002.
[9]	S. L. Phung, A. Bouzerdoum and D. Chai, “A Novel Skin Color Model in Ycbcr Color Space and Its Application to Human Face Detection,” IEEE Inter-national Conference on Image Processing (ICIP’2002), Vol. 1, 2002, pp. 289-292.
[10]	M. Turk and A. Pentland, “Eigenfaces for Recognition,” Journal of Cognitive Neuroscience, Vol. 3, 1991, pp. 71-86.doi:10.1162/jocn.1991.3.1.71
[11]	H. Freeman, “On the Encoding of Arbitrary Geometric Configurations,” in Proceedings of IRE Translation Electron Computer, New York, 1961, pp. 260-268.
[12]	R. C. Gonzales and R. E. Woods, Digital Image Processing, 2nd Ed. Upper Saddle River, N. J.: Prentice-Hall, Inc., 2002.
[13]	Spacek L., Computer Vision Science Research Projects, 2007, Retrieved on July 20, 2012 from Essex University website: http://cswww.essex.ac.uk/mv/allfaces/faces94.html.