Performance analysis of iris-based identification system at the matching score level

IEEE Transactions on Information Forensics and Security

Volumn 1, Issue 2, 2006, Pages 154-168

  Schmid, Natalia A ^a,b   Ketkar, Manasi V ^c   Singh, Harshinder ^d   Cukic, Bojan ^a,b,e  

^a IEEE   (United States)

^b West Virginia University   (United States)

^c International Biometric Group (IBG)   (United States)

^d WEST VIRGINIA UNIVERSITY   (United States)

^e Center for Identification Technology Research   (United States)

Author keywords

Biometrics authentication; Chernoff bound; Hypothesis testing; Iris recognition; Large deviations; Normality test; Performance prediction; Scaling issue

Indexed keywords

BIOMETRICS AUTHENTICATION; CHERNOFF BOUND; IRIS RECOGNITION; PERFORMANCE PREDICTION;

IMAGE CODING; PATTERN RECOGNITION SYSTEMS; PROBABILITY; SECURITY OF DATA; STATISTICAL METHODS; VIDEO CAMERAS;

PATTERN MATCHING;

EID: 33744738243     PISSN: 15566013     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIFS.2006.873603     Document Type: Article

References (38)

1. A. S. Abhyankar, L. A. Hornak, and S. C. Schuckers, "Biorthogonal wavelet-based iris recognition," in Proc. SPIE Symp. Defense and Security Conf. 5779, Orlando, FL, Mar. 28-29, 2005, pp. 59-67.
2. K. Bae, S.-I. Noh, and J. Kim, "Iris feature extraction using independent component analysis," in Proc. Conf. Audio and Video Based Biometric Person Authentication, Guildford, U.K., Jun. 2003, pp. 838-844.
3. R. E. Blahut, Principles and Practice of Information Theory. Reading, MA: Addison-Wesley, 1987.
4. R. M. Bolle, S. Pankanti, J. H. Connell, and N. K. Ratha, "Iris individuality: a partial iris model," in Proc. 17th Int. Conf. Pattern Recognition, Aug. 23-26, 2004, vol. 2, pp. 927-930.
5. J. A. Bucklew, Large Deviation Techniques in Decision, Simulation, and Estimation. New York: Wiley, 1990.
6. J. L. Cambier, Iridian Large Database Performance Tech. Rep. TR-03-002, Aug. 2003.
7. CASIA Iris Image Database ver. 1.0 [Online]. Available: http://www. sinobiometrics.com/casiairis.htm
8. T. M. Cover and J. A. Thomas, Elements of Information Theory, ser. in Telecommunications. New York: Wiley, 1991.
9. J. Daugman, "High confidence visual recognition of persons by a test of statistical independence," IEEE Trans. Pattern Anal. Mach. Intell., vol. 15, no. 11, pp. 1148-1161, Nov. 1993.
10. _, "The importance of being random: statistical principles of iris recognition," Pattern Recog., vol. 36, no. 2, pp. 279-291, 2001.
11. A. Dembo and O. Zeitounim, Large Deviations Techniques and Applications. New York: Springer, 1998.
12. V. Dorairaj, N. A. Schmid, and G. Fahmy, "Performance evaluation of iris based recognition system implementing PCA and ICA techniques," in Proc. SPIE Symp. Defense and Security, Conf. 5779, Orlando, FL, Mar. 28-29, 2005, pp. 51-58.
13. V. Dorairaj, N. A. Schmid, and G. Fahmy, "Performance evaluation of nonideal iris based recognition system implementing ICA encoding," in Proc. Int. Conf. Image Process., Genoa, Italy, Sep. 11-14, 2005, vol. 3. pp. 285-288.
14. Y. Du, B. Bonney, R. Ives, and D. M. Etter, "Analysis of partial iris recognition," in Proc. SPIE Symp. Defense and Security, Conf. 5779, Orlando, FL, Mar. 28-29, 2005, pp. 31-40.
15. C. Fancourt, L. Bogoni, J. Hanna, Y. Guo, N. Takahashi, and U. Jain, "Iris recognition at a distance," in Proc. Conf. Audio Video Based Biometric Person Authentication, Rye Brook, NY, Jul. 20-22, 2005, pp. 1-13.
16. R. C. Gonzales and R.E. Woods, Digital Image Processing. Reading, MA: Addison-Wesley, 1992.
17. R. Gray, Toeplits and Circulant Matrices: A Review. Stanford, CA: Dept. Elect. Eng., Aug. 2002 [Online]. Available: http://ee.stanford. edu/~gray/
18. P. Hall, The Bootstrap and Edgeworth Expansion. New York: Springer, 1992.
19. A. Jain, R. Bolle, and S. Pankanti, Eds., Biometrics: Personal Identification in Networked Society. Norwell, MA: Kluwer, 1999.
20. D. Kirovski and D. Schoenberg, "Iris compression for cryptographically secure person identification," in Proc. Data Compression Conf., 2004, pp. 459-468.
21. B. V. K. V. Kumar, C. Xie, and J. Thornton, "Iris verification using correlation filters," in Proc. Conf. Audio- and Video-Based Personal Identification, 2003, pp. 697-705.
22. B. V. K. V. Kumar, M. Savvides, C. Xie, K. Venkataramani, J. Thornton, and A. Mahalanobis, "Biometric verification with correlation filters," Appl. Opt., vol. 42, no. 10, pp. 391-402, 2004.
23. H. Jarosz, J.-C. Founder, and X. Dupre, "Large-scale identification system design," in Biometric Systems: Technology, Design, and Performance Evaluation, J. Wayman, Ed. et al. New York: Springer, 2004, ch. 9, pp. 263-287.
24. A. Y. Johnson, J. Sun, and A. F. Bobick, "Predicting large population data cumulative match characteristic performance from small population data," in Proc. Conf. Audio and Video Based Biometric Person Authentication, 2003, pp. 821-829.
25. L. Ma, T. Tan, Y. Wang, and D. Zhang, "Personal identification based on iris texture analysis," IEEE Trans. Pattern Anal Mach. Intell., vol. 25, no. 12, pp. 1519-1533, Dec. 2003.
26. _, "Efficient iris recognition by characterizing key local variations," IEEE Trans. Image Process., vol. 13, no. 6, pp. 739-750, Jun. 2004.
27. A. J. Mansfield and J. L. Wayman, Best Practices in Testing and Reporting Performance of Biometric Devices ver. Ver. 2.01, NPL Rep. CMSC 14/02, Nat. Phys. Lab., Aug. 2002.
28. L. Masek, "Recognition of Human Iris Patterns for Biometric Identification" B.S. dissertation, Univ. Western Australia, Crawley, W.A., 2003 [Online]. Available: http://www.csse.uwa.edu.au/~pk/studentprojects/libor/
29. R. J. Muirhead, Aspects of Multivariate Statistical Analysis. Reading, MA: Addison-Wesley, 1982.
30. S.-I. Noh, K. Pae, C. Lee, and J. Kim, "Multiresolution independent component analysis for iris identification," in Proc. Int. Technology Conf. Circuits/Systems, Comp. Commun., Puket, Thailand, 2002.
31. H. V. Poor, An Introduction to Signal Detection and Estimation. New York: Springer, 1994.
32. N. A. Schmid and J. A. O'Sullivan, "Performance prediction methodology for biometric systems using a large deviations approach," IEEE Trans. Signal Process., Supplement Secure Media, vol. 52, no. 10, pp. 3036-3045, Oct. 2004.
33. N. A. Schmid, M. Ketkar, B. Cukic, and H. Singh, "Performance analysis of iris based identification system at the matching score level," in Proc. IEEE Int. Conf. Acoustics, Speech, Signal Processing, Philadelphia, PA, Mar. 18-23, 2005, vol. II, pp. 93-96.
34. S. S. Shapiro and M. B. Wilk, "An analysis of variance test for normality (complete samples)," Biometrika, vol. 52, no. 3-4, pp. 591-611, 1965.
35. H. L. VanTrees, Detection, Estimation, and Modulation Theory. New York: Wiley, 2001.
36. J. L. Wayman, "The cotton ball problem," in Proc. Biometric Consortium Conf., Crystal City Arlington, VA, Sep. 20-22, 2004 [Online]. Available: http://www.biometrics.org/bc2004/Presentations/Conference/1
37. R. P. Wildes, "Automated iris recognition: An emerging biometric technology," Proc. IEEE, vol. 85, no. 9, pp. 1348-1363, Sep. 1997.
38. J. Wayman, A. Jain, D. Maltoni, and D. Maio, Eds., Biometric Systems: Technology, Design, and Performance. Evaluation. New York: Springer, 2004.