Iris Recognition Systems with Reduced Storage and High Accuracy Using Majority Voting and Haar Transform

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (volume 167)

Abstract

Reliable user authentication is becoming an increasingly important task. Biometric based authentication offers several advantages over other authentication methods. Iris based biometric authentication gained more popularity because of its greater accuracy and uniqueness. In this paper, a new method is proposed based on Haar transform and Majority Voting to improve the overall efficiency of existing iris recognition systems in terms of accuracy and storage space. An existing iris recognition algorithm proposed by Libor Masek is used to generate an iris template. Haar transform is applied on those templates to reduce the storage space. Majority voting technique is being performed with target class iriscodes to improve the accuracy of the recognition system. Iriscodes of various combinations are made using different levels of haar decomposition and each combination is represented as a method. Experiments on well known CASIA iris database show that the proposed technique is more efficient and promising.

Keywords

Biometrics Iris Recognition User authentication reduced storage space Haar transform Majority voting 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Pato, J.N., Millet, L.I. (eds.): Biometric Recognition: Challenges and Opportunities. National Research Council, Whither Biometrics Committee (2010)Google Scholar
  2. 2.
    Masek, L.: Recognition of human iris patterns for bio-metric identification. Master thesis, The School of Computer Science and Software Engineering, The university of Western Australia (2003)Google Scholar
  3. 3.
    Daugman, J.: New Methods in Iris Recognition. IEEE Transactions on Systems, Man, Cybernetics 37(5), 1167–1175 (2007)CrossRefGoogle Scholar
  4. 4.
    Wildes, R.P., Asmuth, J.C., Green, G.L., Hsu, S.C., Kolczynski, R.J., Matey, J.R., McBride, S.C.: A machine-vision system for iris recognition. Machine Vision and Applications 9, 1–8 (1996)CrossRefGoogle Scholar
  5. 5.
    He, Z., Tan, T., Sun, Z.: Towards Accurate and Fast Iris Segmentation for Iris Biometrics. IEEE Transactions on PAMI 31(9), 1670–1684 (2009)CrossRefGoogle Scholar
  6. 6.
    Avila, S.C., Reillo, S.R., Martin, I.D.: Iris recognition for biometric identification using dyadic wavelet transform zero-crossing. In: Proceedings of the IEEE 35th International Camahan Conference on Security Technology, pp. 272–277 (2001)Google Scholar
  7. 7.
    Ma, L., Wang, Y., Tan, T.: Iris Recognition Using Circular Symmetric Filters. In: Proceedings of the 16th International Conference on Pattern Recognition, pp. 414–417. IEEE press (2000)Google Scholar
  8. 8.
    Tisse, C.L., Torres, L., Robert, M.: Person Identification Technique Using Human Iris. In: Proceedings of the 15th International Recognition Conference on Vision Interface (2002)Google Scholar
  9. 9.
    Singh, N., Gandhi, D., Singh, D.P.: Iris recognition system using a canny edge detection and a circular hough transform. International Journal of Advances in Engineering & Technology 1, 221–228 (2011)Google Scholar
  10. 10.
    Chinese Academy of Sciences Institute of Automation (2004), CASIA Iris Image Database Version 1.0., http://biometrics.idealtest.org/findTotalDbByMode.do?mode=Iris (accessed October 2011)
  11. 11.
    Kingsbury, N.: The Multi-level Haar Transform. Connexions Web site (2005), http://cnx.org/content/m11089/2.4/ (accessed October 2011)
  12. 12.
    SYRIS Technology Corporation, Technical document about FAR, FRR and EER, Version 1.0 (2004)Google Scholar
  13. 13.
    Vatsa, M., Singh, R., Gupta, P.: Comparison of iris Recognition Algorithms. In: Proceedings of International Conference on Intelligent Sensing and Information Processing, pp. 354–358 (2004)Google Scholar

Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringNational Institute of TechnologyTiruchirappalliIndia

Personalised recommendations