Skip to main content

Combining Left and Right Irises for Personal Authentication

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4679))

Abstract

Traditional personal authentication methods have many instinctive defects. Biometrics is an effective technology to overcome these defects. Among the available biometric approaches, iris recognition is one of the most accurate techniques. Combining the left and the right irises of same persons can improve the authentication accuracy and reduce the spoof attack risks. Furthermore, the fusion need not add any other hardware to the existing iris recognition systems. This paper investigates the feasibility of fusing both irises for personal authentication and the performance of some very simple fusion strategies. The experimental results show that the difference between the left and the right irises of the same persons is close to the difference between the irises captured from different persons. And combining the information of both irises can dramatically improve the authentication accuracy even when the quality of the iris images are not good enough. The results also show that the Minimum and the Product strategies can obtain the perfect performance, i.e. both FARs and FRRs of these two strategies can be reduce to 0%.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Zhang, D.: Automated Biometrics–Technologies and Systems. Kluwer Academic Publishers, Dordrecht (2000)

    Google Scholar 

  2. Jain, A., Bolle, R., Pankanti, S.: Biometrics: Personal Identification in Networked Society. Kluwer Academic Publishers, Dordrecht (1999)

    Google Scholar 

  3. Jain, A., Ross, A., Prabhakar, S.: An introduction to biometric recognition. IEEE Transactions on Circuits and Systems for Video Technology 14, 4–20 (2004)

    Article  Google Scholar 

  4. Daugman, J.: High confidence visual recognition of persons by a test of statistical independence. IEEE Transactions on Pattern Analysis and Machine Intelligence 15, 1148–1161 (1993)

    Article  Google Scholar 

  5. Daugman, J.: How iris recognition works. IEEE Transactions on Circuits and Systems for Video Technology 14, 21–30 (2004)

    Article  Google Scholar 

  6. Wildes, R.: Iris recognition: an emerging biometric technology. Proceedings of the IEEE 85, 1348–1363 (1997)

    Article  Google Scholar 

  7. Boles, W., Boashash, B.: A human identification technique using images of the iris and wavelet transform. IEEE Transactions on Signal Processing 46, 1185–1188 (1998)

    Article  Google Scholar 

  8. Ma, L., Tan, T., Wang, Y., Zhang, D.: Personal identification based on iris texture analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 25, 1519–1533 (2003)

    Article  Google Scholar 

  9. Ma, L., Tan, T., Wang, Y., Zhang, D.: Local intensity variation analysis for iris recognition. Pattern Recognition 37, 1287–1298 (2004)

    Article  Google Scholar 

  10. Ma, L., Tan, T., Wang, Y., Zhang, D.: Efficient iris recognition by characterizing key local variations. IEEE Transactions on Image Processing 13, 739–749 (2004)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Alan L. Yuille Song-Chun Zhu Daniel Cremers Yongtian Wang

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Wu, X., Wang, K., Zhang, D., Qi, N. (2007). Combining Left and Right Irises for Personal Authentication. In: Yuille, A.L., Zhu, SC., Cremers, D., Wang, Y. (eds) Energy Minimization Methods in Computer Vision and Pattern Recognition. EMMCVPR 2007. Lecture Notes in Computer Science, vol 4679. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74198-5_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-74198-5_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74195-4

  • Online ISBN: 978-3-540-74198-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics