The week's pick
Reseach Article
Fake Iris Detection: A Holistic Approach
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 19 - Number 2 |
| Year of Publication: 2011 |
| Authors: Rajesh Bodade, Sanjay Talbar |
10.5120/2337-3047
|
Rajesh Bodade, Sanjay Talbar . Fake Iris Detection: A Holistic Approach. International Journal of Computer Applications. 19, 2 ( April 2011), 1-7. DOI=10.5120/2337-3047
Abstract
There is tremendous interest in improved methods of reliable and secure identification of people using biometrics. Although, iris is believed to allow very high accuracy, various experiments showed an alarming lack of anti-spoofing mechanisms in devices already protecting many sensitive areas all over the world. This enforces the need for aliveness detection methodology to be quickly introduced. In this paper, all possible types of fake iris has been identified. Previously published work in this field had concentrated only either on active or passive methods for fake iris detection. This has visible shortcomings of detecting only specific types of fake irises corresponding to each method and not of all kinds. This paper proposes a composite method, with promising results, to overcome the shortcomings of existing methods. The FAR and FRR values of the proposed method on realistic database of 160 images are 0.625% and 0.625% respectively. A notable achievement of this work is development of robust iris segmentation algorithm having inherent capability of fake iris detection.
References
- Anil K. Jain, ArunRoss, and Salil Prabhakar: An Introduction to Biometric Recognition, IEEE Transactions on Circuits and Systems for Video Technologies, vol. 14, no. 1, pp. 4-20, (2004)
- Kevin W. Bowyer, Karen Hollingsworth, Patrick J. Flynn, Image understanding for iris biometrics:A Survey, J. Computer Vision and Image Understanding, vol 110, no. 2, pp. 281-307, May 2008 Elsevier Science Inc. New York (2008)
- R. Johnston : Can iris patterns be used to identify people?, Chemical and Laser Sciences Division, Los Alamos National Laboratory, Annual Report, LA-12331-PR, June 1992, pp. 81–86 (1992).
- Lisa Thalheim, Jan Krissler, and Peter-Michael Ziegler : Biometric Access Protection Devices and their Programs Put to the Test , c’t 11/2002, page 114 (available online at: http://www.larc.usp.br/~pbarreto/Leitura%202%20-%20Biometria.pdf)
- T. Matsumoto : Impact of Artificial Gummy Fingers on Fingerprint Systems, Proc. SPIE, vol.4677, pp. 275-289 (2002).
- John Daugman, "Anti-spoofing Liveness Detection", (available on-line at: http://www.cl.cam.ac.uk/users/igdl 000/countermeasures.pdf)
- Daugman, J.: Iris Recognition and Anti-Spoofing Countermeasures. In: 7th International Biometrics Conference, London (2004)
- S. Lee ,Kang Ryoung Park, Jaihie Kim. : A Study on Fake Iris Detection based on the Reflectance of the Iris to the Sclera for Iris Recognition , In: Conf. ITC¬-CSCC-2005, , Jeju Island, South Korea, pp. 1555-1556, (2005)
- Andrzej Pacut and Adam Czajka : Aliveness Detection for Iris Biometrics, In: Proc. of IEEE International Carnahan Conf on Security Technology , pp. 122-129, (2006)
- Manfred Clynes and Michael Cohn: Color dynamics of the pupil, Annals of New York Academy of Science, vol. 156, pp. 931-950, April 1969, John Wiely Online Library (2006)
- Rajesh Bodade and Sanjay Talbar,: Iris Recognition using Combination of Dual Tree Rotated Complex Wavelet and Dual Tree Complex Wavelet, In: Proc. Of IEEE International Conference on Communication-2009, (ICC-2009), Dresden, Germany, June 2009, pp. 1-5, IEEE Press (2009)
- J. Daugman,: How iris recognition works, IEEE Transactions on Circuits and Systems for Video Technology, vol. 14, pp. 21–30, January 2004. (2004)
- Iris Recognition: An Emerging Biometric Technology, Richard P Wildes, Proceedings of the IEEE, Vol. 85, No. 9, September 1997
- Rajesh Bodade and Sanjay Talbar, :Segmentation for Iris Localisation: A Novel Approach Suitable for Fake Iris Detection, In Proc. of Third International Conference on Pattern Recognition and Machine Intelligence-2009, (PReMI’09), New Delhi, India, 16-20 Dec 2009, LNCS, Vol. 5909/2009, PP. 476-482, Springer (2009)
- Li Ma, Tieniu Tan, Yunhong Wang, and Dexin Zhang. : Personal identification based on iris texture analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, no. 12, PP. 2519–2533, (2003)
- High contrast Iris image database, http://phoenix.inf.upol.cz/iris/download/
- Chinese Academy of Sciences Institute of Automation, http://www.sinobiometrics.com
- Hugo Proenc¸a and Lu´ıs A. Alexandre. UBIRIS: iris image database, http://iris.di.ubi.pt
- V. Ekaterina : Estimation of melanin content in iris of human eye: Prognosis for glaucoma diagnostics. In: Proc. of SPIE, vol. 5688, pp. 302–311, (2005).
- Masek L, Kovesi P: MATLAB sourse code for a Biometric Identification System Based on Iris Paterns, The school of Computer Science and Software Engineering, The University of Western Austrilia, (2003)
- Rajesh M Bodade and Sanjay N Talbar: Iris Recognition Using Multi-Directional Wavelets: A Novel Approach’, International Journal of Advances in Engineering Sciences (special issue on Image Processing) Sect. C (3), July-September 2008, ISSN: 0973-9041.
Index Terms
Keywords