IRIS RECOGNITION BY USING HCT, PCA, HAMMING DISTANCE

Volume: 2    Issue: 3

Year of Publication: 2015

Pages: (11-16)

Authors: Ravneet Kaur, Sanjay Madaan

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Abstract

In this paper, we have developed a system that can recognize human iris patterns and an analysis of the results is done. A novel mechanism has been used for implementation of the system. Feature training has been used to extract the most discriminating features of the iris and is done using HCT, HAMMING DISTANCE and PCA scheme. And finally the biometric templates are secret using CANNY edge detection which tells us whether the two iris images are same or not and on the basis of that performance metric are evaluated like FAR, FRR and Accuracy. The whole simulation is taken place in the MATLAB environment.

References

1. LeninaBirgale and M. Kokare, 2010. Iris Recognition without Iris Normalization. Journal of Computer Science 6, pp. 1042-1047.

2. J.L. Wayman, “Fundamentals of Biometric Authentication Technologies”, International Journal of Image and Graphics, Vol. 1, No. 1, pp. 93-113, 2011.

3. P.J. Philips, P. Grother, R. J. Micheals, D. M. Blackburn, E. Tabassi, and J. M. Bone, “FRVT 2009: Overview and Summary” http://www.frvt.org/FRVT2002/documents.html.

4. E.Sridevi, B.Aruna, P. Sowjanya, “An Exploration of Vascular Biometrics” IJECT (International Journal of Electronics & Communication Technology)Vol. 2, SP-1, Dec . 2011,ISSN : 2230-7109(Online) | ISSN : 2230- 9543(Print) IJECT Vol. 2, SP-1, Dec . 2011 , pp.181-184.

5. Jiali Cui, Yunhong Wang, JunZhou Huang, Tieniu Tan and Zhenan Sun, “An Iris Image Synthesis Method Based on PCA and Super-resolution”, IEEE CS Proceedings of the 17th International Conference on Pattern Recognition (ICPR’04), 23-26 August 2004, Cambridge, UK, Vol. 4, pp. 471-474.

6. Elgamal, Mahmoud, and Nasser Al-Biqami. \"An efficient feature extraction method for iris recognition based on wavelet transformation.\" International Journal of Computer and Information Technology 2.03 (2013): 521-527.

7. Kefeng FAN, Qingqi Pei, Wei MO, Xinhua Zhao, and Qifeng Sun, “An Efficient Automatic Iris Image Acquisition and Preprocessing System”, Proceedings of the 2006 IEEE International Conference on Mechatronics and Automation, June 25-28, 2006, Luoyang, China, pp. 1779-1784.

8. Shi, Jin-Xin, and Xiao-Feng Gu. \"The comparison of iris recognition using principal component analysis, independent component analysis and Gabor wavelets.\" Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on. Vol. 1. IEEE, 2010.

9. Raja, Kiran B., R. Raghavendra, and Christoph Busch. \"Binarized statistical features for improved iris and periocular recognition in visible spectrum.\"Biometrics and Forensics (IWBF), 2014 International Workshop on. IEEE, 2014.

10. Lye Wi Liam, Ali Chekima, Liau Chung Fan and Jamal Ahmad Dargham, “Iris Recognition using Self-Organizing Neural Network”, IEEE 2002 Student Conference on Research and Development Proceedings, Shah Alam, Malaysia, pp. 169-172.

11. L. Ma, Y.Wang.T. Tan. “Iris recognition using circular symmetric filters.” National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 2002.

12. Y.Zhu, T. Tan, and Y. Wang, “Biometric Personal Identification Based on Iris Patterns”, International Conference on Pattern Recognition (ICPR’00)-Volume2.p.2801, Sept. 2000.

13. Tisse C.L.;Martin L.;Torres L.;Robert M.,”Person Identification Technique Using Human Iris Recognition”,St Journal of System Research, Vol.4,pp.67_75,2003.

14. Daugman, J,”High Confidence Visual Recognition of Persons by a Test of Statistical Independence, “IEEE Transactions on pattern analysis and Machine intelligence, vol. 15, no. 11, November 2, June 2001, pp. 1148-1161.

15. Gonzalez,R.C., Woods,R.E,Digital Image Processing, 2nd ed., Prentice Hall (2002).

16. Lim, S.,Lee, K., Byeon, O., Kim, T, “Efficient Iris Recognition through Improvement of Feature Vector and Classifier”, ETRJ Journal, Volume 23, Number 2, June 2001, pp. 61-70.

17. Atul Bansal, Ravinder Agarwal, R.K. Sharma, “FAR and FRR Based Analysis of Iris Recognition System” , IEEE International Conference of Signal Processing, Computing and control, Vol. 1 in 2012.

Keywords

CANNY edge detector, Hough Circular transform (HCT), Principal Component Analysis (PCA), Hamming Distance.