Skip to main content

Iris Recognition for Biometric Personal Identification Using Neural Networks

  • Conference paper
Artificial Neural Networks – ICANN 2007 (ICANN 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4669))

Included in the following conference series:

Abstract

This paper presents iris recognition for personal identification using neural networks. Iris recognition system consists of localization of the iris region and generation of data set of iris images and then iris pattern recognition. One of the problems in iris recognition is fast and accurate localization of the iris image. In this paper, fast algorithm is used for the localization of the inner and outer boundaries of the iris region. Located iris is extracted from an eye image, and, after normalization and enhancement it is represented by a data set. Using this data set a neural network is applied for the classification of iris patterns. Results of simulations illustrate the effectiveness of the neural system in personal identification.

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

Access this chapter

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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Jain, A., Bolle, R., Pankanti, S. (eds.): Biometrics: Personal Identification in a Networked Society. Kluwer, Dordrecht (1999)

    Google Scholar 

  2. Adler, F.: Physiology of the Eye: Clinical Application, fourth ed. London: The C.V. Mosby Company (1965)

    Google Scholar 

  3. Daugman, J.: Biometric Personal Identification System Based on Iris Analysis, United States Patent, no. 5291560 (1994)

    Google Scholar 

  4. Daugman, J.: Statistical Richness of Visual Phase Information: Update on Recognizing Persons by Iris Patterns, Int’l J. Computer Vision 45(1), 25–38 (2001)

    Article  MATH  Google Scholar 

  5. Daugman, J.: Demodulation by Complex-Valued Wavelets for Stochastic Pattern Recognition, Int J. Wavelets, Multiresolution and Information Processing 1(1), 1–17 (2003)

    Article  MATH  Google Scholar 

  6. Daugman, J.: How Iris Recognition Works, University of Cambridge (2001)

    Google Scholar 

  7. Masek, L.: Recognition of Human Iris Patterns for Biometric Identification. School of Computer Science and Soft Engineering, The University of Western Australia (2003)

    Google Scholar 

  8. Wildes, R., Asmuth, J., Green, G., Hsu, S., Kolczynski, R., Matey, J., McBride, S.: A Machine-Vision System for Iris Recognition. Machine Vision and Applications 9, 1–8 (1996)

    Google Scholar 

  9. Boles, W., Boashash, B.: A Human Identification Technique Using Images of the Iris and Wavelet Transform. IEEE Trans. Signal Processing 46(4), 1185–1188 (1998)

    Article  Google Scholar 

  10. Ma, L., Wang, Y.H., Tan, T.N.: Iris recognition based on multichannel Gabor filtering. In: Proceedings of the Fifth Asian Conference on Computer Vision, Australia, pp. 279–283 (2002)

    Google Scholar 

  11. Lim, S., Lee, K., Byeon, O., Kim, T.: Efficient Iris Recognition through Improvement of Feature Vector and Classifier. ETRI J. 23(2), 61–70 (2001)

    Google Scholar 

  12. Ma, L., Tan, T., Wang, Y., Zhang, D.: Personal Identification Based on Iris Texture Analysis. IEEE Transaction on Pattern Analysis and Machine Intelligence 25(12) (2003)

    Google Scholar 

  13. Huang, Y.-P., Luo, S.-W., Chen, E.-Y.: An Efficient Iris Recognition System. In: Proceedings of the First International Conference on Machine Learning and Cybernetics, Beijing (November 2003)

    Google Scholar 

  14. Wang, Y., Han, J.-Q.: Iris Recognition Using Independent Component Analysis. In: Proceedings of the Fourth International Conference on Machine Learning and Cybernetics, Guangzhou (2005)

    Google Scholar 

  15. Sanchez-Avila, C., Sanchez-Reillo, R.: Iris-Based Biometric Recognition Using Dyadic Wavelet Transform. IEEE Aerospace and Electronic Systems Magazine, 3–6 (2002)

    Google Scholar 

  16. Daugman, J., Downing, C.: Recognizing iris texture by phase demodulation. IEEE Colloquium on Image Processing for Biometric Measurement 2, 1–8 (1994)

    Google Scholar 

  17. Chavez, R.F.L., Iano, Y., Sablon, V.B.: Process of Recognition of Human Iris: Fast Segmentation of Iris, www.decom.fee.unicamp.br/~rlarico/iris/localizationiris.pdf

Download references

Author information

Authors and Affiliations

Authors

Editor information

Joaquim Marques de Sá Luís A. Alexandre Włodzisław Duch Danilo Mandic

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Abiyev, R.H., Altunkaya, K. (2007). Iris Recognition for Biometric Personal Identification Using Neural Networks. In: de Sá, J.M., Alexandre, L.A., Duch, W., Mandic, D. (eds) Artificial Neural Networks – ICANN 2007. ICANN 2007. Lecture Notes in Computer Science, vol 4669. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74695-9_57

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-74695-9_57

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74693-5

  • Online ISBN: 978-3-540-74695-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics