Advertisement

Simulating the Influences of Aging and Ocular Disease on Biometric Recognition Performance

  • Halvor Borgen
  • Patrick Bours
  • Stephen D. Wolthusen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5558)

Abstract

Many applications of ocular biometrics require long-term stability, yet only limited data on the effects of disease and aging on the error rates of ocular biometrics is currently available. Based on pathologies simulated using image manipulation validated by opthalmology and optometry specialists, the present paper reports on the effects that selected common ocular diseases and age-related pathologies have on the recognition performance of two widely used iris and retina recognition algorithms, finding the algorithms to be robust against many even highly visible pathologies, permitting acceptable re-enrolment intervals for most disease progressions.

Keywords

Diabetic Retinopathy Recognition Performance Iris Image Trabecular Meshwork Ocular Disease 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Download to read the full conference paper text

References

  1. 1.
    Bundesamt für Sicherheit in der Informationstechnik: Public Final Report: Evaluation of Fingerprint Recognition Technologies — BioFinger. Technical report, BSI and BKA, Bonn, Germany (August 2004)Google Scholar
  2. 2.
    Proença, H., Alexandre, L.A.: UBIRIS: A Noisy Iris Image Database. In: Roli, F., Vitulano, S. (eds.) ICIAP 2005. LNCS, vol. 3617, pp. 970–977. Springer, Heidelberg (2005)Google Scholar
  3. 3.
    Simon, C., Goldstein, I.: A New Scientific Method of Identification. New York State Journal of Medicine 35(18), 901–906 (1935)Google Scholar
  4. 4.
    Simon, C.: The Retina Method of Authentication. Series 4: Unpublished Writings by Carleton Simon, 1900–1925, 1935–1938, 1940–1945, Files A-S. M. E. Grenander Department of Special Collections & Archives, State University of New York at Albany (1936)Google Scholar
  5. 5.
    Bolle, R., Pankanti, S., Jain, A.K.: Biometrics: Personal Identification in a Networked World. Kluwer Academic Publishers, Dordrecht (1998)Google Scholar
  6. 6.
    Woodward, J.D., Orlans, N.M., Higgins, P.T.: Biometrics: Identity Assurance in the Information Age. Osborne McGraw Hill, New York (2003)Google Scholar
  7. 7.
    Hill, R.B.: Apparatus and method for identifying individuals through their retinal vasculature pattern. U.S. Patent 4109237 (1978)Google Scholar
  8. 8.
    Hill, R.B.: Fovea-centered eye fundus scanner. U.S. Patent 4620318 (1986)Google Scholar
  9. 9.
    Samples, J.R., Hill, R.V.: Use of infrared fundus reflection for an identification device. American Journal of Ophthalmology 98(5), 636–640 (1984)Google Scholar
  10. 10.
    Borgen, H., Bours, P., Wolthusen, S.D.: Visible-Spectrum Biometric Retina Recognition. In: Proc. 4th Int’l. Conf. IIH-MSP, Harbin, China, pp. 1056–1062. IEEE Press, Los Alamitos (2008)Google Scholar
  11. 11.
    Wildes, R.P.: Iris Recognition: An Emerging Biometric Technology. Proc. IEEE 85(9), 1348–1363 (1997)Google Scholar
  12. 12.
    Flom, L., Safir, A.: Iris Recognition System. U.S. Patent 4641349 (1987)Google Scholar
  13. 13.
    Daugman, J.: How Iris Recognition Works. IEEE Transactions on Circuits and Systems for Video Technology 14(1), 21–30 (2004)Google Scholar
  14. 14.
    Daugman, J.: Probing the Uniqueness and Randomness of IrisCodes: Results From 200 Billion Iris Pair Comparisons. Proc. IEEE 94(11), 1927–1935 (2006)Google Scholar
  15. 15.
    Nanavati, S., Thieme, M., Nanavati, R.: Biometrics: Identity Verification in a Networked World. John Wiley & Sons, New York (2002)Google Scholar
  16. 16.
    Wayman, J.L., Jain, A.K., Maltoni, D., Maio, D.: Biometric Systems: Technology, Design and Performance Evaluation. Springer-Verlag, Berlin (2005)Google Scholar
  17. 17.
    Masek, L., Kovesi, P.: MatLab Source Code for a Biometric Identification System Based on Iris Patterns. B.Sc. thesis, U. of Western Australia (May 2003)Google Scholar
  18. 18.
    Cole III, R.M.: Glaucoma. Review of Optometry 143(5) (May 2006)Google Scholar
  19. 19.
    Teus, M.A., Arranz-Márquez, E., Lucea-Suescun, P.: Incidence of iris colour change in latanoprost treated eyes. British Journal of Ophthalmology 86(10), 1085–1088 (2002)Google Scholar
  20. 20.
    Nowak, J.Z.: Age-Related Macular Degeneration (AMD): Pathogenesis and Therapy. Pharmacological Reports 58(3), 353–363 (2006)Google Scholar
  21. 21.
    Gehrs, K.M., Anderson, D.H., Johnson, L.V., Hageman, G.S.: Age-related macular degeneration – Emerging pathogenetic and therapeutic concepts. Annals of Medicine 38(7), 450–471 (2006)Google Scholar
  22. 22.
    Borgen, H.: The Effects of Eye Disease and Aging of the Eye on Biometric Authentication. Master’s thesis, Gjøvik University College, Gjøvik, Norway (July 2007)Google Scholar
  23. 23.
    Allen, D., Vasavada, A.: Cataract and surgery for cataract. British Medical Journal 333(7559), 128–132 (2006)Google Scholar
  24. 24.
    Torpy, J.M., Glass, T.J., Glass, R.M.: Retinopathy. Journal of the American Medical Association 293(1), 128 (2005)Google Scholar
  25. 25.
    Gariano, R.F., Gardner, T.W.: Retinal angiogenesis in development and disease. Nature 438(7070), 960–966 (2005)Google Scholar
  26. 26.
    Pavan-Langston, D.: Diagnosis and therapy of common eye infections: Bacterial, viral, fungal. Comprehensive Therapy 9(5), 33–42 (1983)Google Scholar
  27. 27.
    Smith, K.N.: Analysis of Pigmentation and Wavefront Coding Acquisition in Iris Recognition. Master’s thesis, West Virginia U., Morgantown, WV, USA (May 2007)Google Scholar
  28. 28.
    Roizenblatt, R., Schor, P., Dante, F., Roizenblatt, J., Belfort Jr., R.: Iris recognition as a biometric method after cataract surgery. BioMedical Engineering OnLine 3(2), 1–7 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Halvor Borgen
    • 1
  • Patrick Bours
    • 1
  • Stephen D. Wolthusen
    • 1
    • 2
  1. 1.Norwegian Information Security LaboratoryGjøvik University CollegeGjøvikNorway
  2. 2.Information Security Group, Department of Mathematics, Royal HollowayUniversity of LondonEghamUnited Kingdom

Personalised recommendations

Cite paper