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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Vol. 43, Iss. 2 — Jan. 10, 2004
  • pp: 391–402

Biometric verification with correlation filters

B. V. K. Vijaya Kumar, Marios Savvides, Chunyan Xie, Krithika Venkataramani, Jason Thornton, and Abhijit Mahalanobis  »View Author Affiliations


Applied Optics, Vol. 43, Issue 2, pp. 391-402 (2004)
http://dx.doi.org/10.1364/AO.43.000391


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Abstract

Using biometrics for subject verification can significantly improve security over that of approaches based on passwords and personal identification numbers, both of which people tend to lose or forget. In biometric verification the system tries to match an input biometric (such as a fingerprint, face image, or iris image) to a stored biometric template. Thus correlation filter techniques are attractive candidates for the matching precision needed in biometric verification. In particular, advanced correlation filters, such as synthetic discriminant function filters, can offer very good matching performance in the presence of variability in these biometric images (e.g., facial expressions, illumination changes, etc.). We investigate the performance of advanced correlation filters for face, fingerprint, and iris biometric verification.

© 2004 Optical Society of America

OCIS Codes
(100.6740) Image processing : Synthetic discrimination functions

History
Original Manuscript: May 16, 2003
Revised Manuscript: September 16, 2003
Published: January 10, 2004

Citation
B. V. K. Vijaya Kumar, Marios Savvides, Chunyan Xie, Krithika Venkataramani, Jason Thornton, and Abhijit Mahalanobis, "Biometric verification with correlation filters," Appl. Opt. 43, 391-402 (2004)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-43-2-391


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References

  1. P. J. Philips, P. Grother, R. Micheals, D. M. Blackburn, E. Tabassi, M. Bone, “Face recognition vendor test 2002: overview and summary,” http://www.frvt2002.org .
  2. B. V. K. Vijaya Kumar, “Tutorial survey of composite filter designs for optical correlators,” Appl. Opt. 31, 4773–4801 (1992). [CrossRef]
  3. D. O. North, “An analysis of the factors which determine signal/noise discriminations in pulsed carrier systems,” Proc. IEEE 51, 1016–1027 (1963). [CrossRef]
  4. A. VanderLugt, “Signal detection by complex spatial filtering,” IEEE Trans. Inf. Th. 10, 139–145 (1964). [CrossRef]
  5. C. F. Hester, D. Casasent, “Multivariant technique for multiclass pattern recognition,” Appl. Opt. 19, 1758–1761 (1980). [CrossRef] [PubMed]
  6. B. V. K. Vijaya Kumar, “Minimum variance synthetic discriminant functions,” J. Opt. Soc. Am. A 3, 1579–1584 (1986). [CrossRef]
  7. A. Mahalanobis, B. V. K. Vijaya Kumar, D. Casasent, “Minimum average correlation energy filters,” Appl. Opt. 26, 3633–3630 (1987). [CrossRef] [PubMed]
  8. P. Réfrégier, “Optimal trade-off filters for noise robustness, sharpness of the correlation peak, and Horner efficiency,” Opt. Lett. 16, 829–831 (1991). [CrossRef] [PubMed]
  9. A. Mahalanobis, B. V. K. Vijaya Kumar, S. R. F. Sims, J. F. Epperson, “Unconstrained correlation filters,” Appl. Opt. 33, 3751–3759 (1994). [CrossRef] [PubMed]
  10. A. Mahalanobis, B. V. K. Vijaya Kumar, S. R. F. Sims, “Distance classifier correlation filters for distortion tolerance, discrimination and clutter rejection,” in Photonics for Processors, Neural Networks, and Memories, J. L. Horner, B. Javidi, S. T. Kowel, W. J. Miceli, eds., Proc. SPIE2026, 325–335 (1993). [CrossRef]
  11. B. V. K. Vijaya Kumar, A. Mahalanobis, A. Takessian, “Optimal tradeoff circular harmonic function correlation filter methods providing controlled in-plane rotation response,” IEEE Trans. Image Process. 9, 1025–1034 (2000). [CrossRef]
  12. A. Mahalanobis, B. V. K. Vijaya Kumar, “Polynomial filters for higher-order and multi-input information fusion,” in Proceedings of the Eleventh Euro-American Optoelectronic Workshop, Spain, June1997, pp. 221–231.
  13. A. V. Oppenheim, R. W. Schaffer, Digital Signal Processing (Prentice-Hall, Englewood Cliffs, N.J., 1975).
  14. Advanced Multimedia Processing Laboratory web page, Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, Pa. (November2003), http://amp.ece.cmu.edu .
  15. F. J. Huang, T. Chen, “Tracking of multiple faces for human-computer interfaces and virtual environments,” IEEE International Conference on Multimedia and Expo, (Institute of Electrical and Electronics Engineers, New York, 2000), pp. 1563–1566.
  16. M. Turk, A. Pentland, “Eigenfaces for recognition,” J. Cogn. Neurosci. 3, 71–86 (1991). [CrossRef]
  17. X. Liu, T. Chen, B. V. K. Vijaya Kumar, “Face authentication for multiple subjects using eigenflow,” Pattern Recogn. 36, 313–328 (2003). [CrossRef]
  18. T. Sim, S. Baker, M. Bsat, “The CMU pose, illumination, and expression (PIE) database of human faces,” Technical Report CMU-RI-TR-01-02 (Robotics Institute, Carnegie Mellon University, Pittsburgh, Pa., 2001).
  19. P. Belhumeur, J. Hespanha, D. Kriegman, “Eigenfaces vs fisherfaces: recognition using class specific linear projection,” IEEE Trans. Pattern Anal. Mach. Intell. 19, 711–720 (1997). [CrossRef]
  20. A. Jain, L. Hong, R. Bolle, “On-line fingerprint verification,” IEEE Trans. Pattern Anal. Mach. Intell. 19, 302–314 (1997). [CrossRef]
  21. A. Jain, L. Hong, S. Pankati, R. Bolle, “An identity-authentication system using fingerprints,” Proc. IEEE 85, 1365–1388 (1997). [CrossRef]
  22. C. I. Watson, NIST Special Database 24—Live-Scan Digital Video Fingerprint Database, 1998, http://www.nist.gov/srd/nists24.htm .
  23. J. G. Daugman, “High confidence visual recognition of persons by a test of statistical independence,” IEEE Trans. Pattern Anal. Mach. 15, 1148–1161 (1993). [CrossRef]
  24. Miles Research Laboratory, http://www.milesresearch.com .

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