The paper proposes a novel technique for iris
recognition using texture and phase features. Texture features are
extracted on the normalized iris strip using Haar Wavelet while phase
features are obtained using LOG Gabor Wavelet. The matching
scores generated from individual modules are combined using sum of
score technique. The system is tested on database obtained from Bath
University and Indian Institute of Technology Kanpur and is giving
an accuracy of 95.62% and 97.66% respectively. The FAR and FRR
of the combined system is also reduced comparatively.
[1] L. Flom, and A. Safir, "Iris Recognition System," U.S Patent No.
4641349. U.S Government Printing Office, Washington DC, 1987.
[2] J. Daugman, "Biometric Personal Identification System Based on Iris
Analysis," US patent 5291560, Patent and Trademark Office,
Washington, D.C., 1994.
[3] L. Ma, T. Tan, Y. Wang, and D. Zhang, "Personal identification based
on iris texture analysis," In IEEE Pattern Analysis and Machine
Intelligence, volume 25, pp. 1519-1533, 2003.
[4] C. Kimme, D. Ballard, and J. Sklansky, "Finding circles by an array of
accumulators," ACM Commununication, volume 18(2), pp. 120-122,
1975.
[5] M. Rizon, H. Yazid, P. Saad, A. Y. Md. Shakaff, A. S. Rahman, M.
Sugisaka, S. Yaacob, M. M. Rozailan, and M. Karthigayan, "Object
detection using circular hough transform," American Journal of Applied
Sciences, volume 2(12), 2005.
[6] S. Lim, K. Lee, O. Byeon, and T. Kim, "Efficient iris recognition
through improvement of feature vector and classifier," ETRI journal,
volume 23(2), pp. 61-70, 2001.
[7] D. J. Field, "Relations between the statistics of natural images and the
response properties of cortical cells," J. Opt. Soc. Am. A, volume 4(12),
pp. 23-79, 1987.
[8] J. Daugman, "Statistical Richness of Visual Phase Information: Update
on Recognizing Persons by Iris Patterns," International Journal on
Computer Vision, volume 45(1), pp. 25-38, 2001.
[9] Y. Zhu, T. Tan, and Y. Wang, "Biometric personal identification based
on iris patterns," Proceedings of 15th International Conference on
Pattern Recognition, volume 2, pp. 801-804, 2000.
[10] W. W. Boles, and B. Boashash, "A human identification technique using
images of the iris and wavelet transform," IEEE Transactions on Signal
Processing, volume 46(4), pp. 1185-1188, 1998.
[11] L. Ma, T. Tan, Y. Wang, and D. Zhang, "Local intensity variation
analysis for iris recognition," Pattern Recognition, volume 37(6), pp.
1287-1298, 2004.
[12] L. Masek, "Recognition of Human Iris Patterns for Biometrics
Identification," B.Eng's thesis, University of Western Australia, 2003.
[13] http://www.bath.ac.uk/elec-eng/research/sipg/irisweb/database.htm
[14] J. Daugman, "The importance of being random: Statistical principles of
iris recognition," Pattern Recognition, volume 36(2), pp. 279-291, 2003.
[1] L. Flom, and A. Safir, "Iris Recognition System," U.S Patent No.
4641349. U.S Government Printing Office, Washington DC, 1987.
[2] J. Daugman, "Biometric Personal Identification System Based on Iris
Analysis," US patent 5291560, Patent and Trademark Office,
Washington, D.C., 1994.
[3] L. Ma, T. Tan, Y. Wang, and D. Zhang, "Personal identification based
on iris texture analysis," In IEEE Pattern Analysis and Machine
Intelligence, volume 25, pp. 1519-1533, 2003.
[4] C. Kimme, D. Ballard, and J. Sklansky, "Finding circles by an array of
accumulators," ACM Commununication, volume 18(2), pp. 120-122,
1975.
[5] M. Rizon, H. Yazid, P. Saad, A. Y. Md. Shakaff, A. S. Rahman, M.
Sugisaka, S. Yaacob, M. M. Rozailan, and M. Karthigayan, "Object
detection using circular hough transform," American Journal of Applied
Sciences, volume 2(12), 2005.
[6] S. Lim, K. Lee, O. Byeon, and T. Kim, "Efficient iris recognition
through improvement of feature vector and classifier," ETRI journal,
volume 23(2), pp. 61-70, 2001.
[7] D. J. Field, "Relations between the statistics of natural images and the
response properties of cortical cells," J. Opt. Soc. Am. A, volume 4(12),
pp. 23-79, 1987.
[8] J. Daugman, "Statistical Richness of Visual Phase Information: Update
on Recognizing Persons by Iris Patterns," International Journal on
Computer Vision, volume 45(1), pp. 25-38, 2001.
[9] Y. Zhu, T. Tan, and Y. Wang, "Biometric personal identification based
on iris patterns," Proceedings of 15th International Conference on
Pattern Recognition, volume 2, pp. 801-804, 2000.
[10] W. W. Boles, and B. Boashash, "A human identification technique using
images of the iris and wavelet transform," IEEE Transactions on Signal
Processing, volume 46(4), pp. 1185-1188, 1998.
[11] L. Ma, T. Tan, Y. Wang, and D. Zhang, "Local intensity variation
analysis for iris recognition," Pattern Recognition, volume 37(6), pp.
1287-1298, 2004.
[12] L. Masek, "Recognition of Human Iris Patterns for Biometrics
Identification," B.Eng's thesis, University of Western Australia, 2003.
[13] http://www.bath.ac.uk/elec-eng/research/sipg/irisweb/database.htm
[14] J. Daugman, "The importance of being random: Statistical principles of
iris recognition," Pattern Recognition, volume 36(2), pp. 279-291, 2003.
@article{"International Journal of Information, Control and Computer Sciences:52466", author = "Hunny Mehrotra and Banshidhar Majhi and Phalguni Gupta", title = "Multi-algorithmic Iris Authentication System", abstract = "The paper proposes a novel technique for iris
recognition using texture and phase features. Texture features are
extracted on the normalized iris strip using Haar Wavelet while phase
features are obtained using LOG Gabor Wavelet. The matching
scores generated from individual modules are combined using sum of
score technique. The system is tested on database obtained from Bath
University and Indian Institute of Technology Kanpur and is giving
an accuracy of 95.62% and 97.66% respectively. The FAR and FRR
of the combined system is also reduced comparatively.", keywords = "Fusion, Haar Wavelet, Iris, LOG Gabor Wavelet,Phase, Texture.", volume = "2", number = "8", pages = "2603-5", }
