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Towards enhancing the security and accuracy of iris recognition systems

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Abstract

The intricate structure of the iris constitutes a powerful biometric characteristic utilized by iris recognition algorithms to extract discriminative biometric templates. Iris recognition is field-proven but consequential issues, e.g. privacy protection or recognition in unconstrained environments, still to be solved, raise the need for further investigations. In this paper different improvements focused on template protection and biometric comparators are presented. Experimental evaluations are performed on a public dataset confirming the soundness of proposed enhancements.

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Literatur

  1. K.W. Bowyer, K. Hollingsworth, and P.J. Flynn. Image understanding for iris biometrics: A survey. Computer Vision and Image Understanding, 110(2):281–307, 2007.

    Article  Google Scholar 

  2. J. Daugman, J. (2004). How iris recognition works, IEEE Transactions on Circiuts and Systems for Video Technology 14(1): 21–30.

    Article  Google Scholar 

  3. F. Hao, R. Anderson, and J. Daugman. Combining Cryptography with Biometrics Effectively. IEEE Transactions on Computers, 55(9):1081–1088, 2006.

    Article  Google Scholar 

  4. A. Juels and M. Wattenberg. A fuzzy commitment scheme. In Proc. 6th ACM Conf. on Computer and Communications Security, pages 28–36. ACM, 1999.

    Google Scholar 

  5. L. Masek. Recognition of Human Iris Patterns for Biometric Identification. Master’s thesis, University of Western Australia, 2003.

    Google Scholar 

  6. C. Rathgeb and A. Uhl. A Survey on Biometric Cryptosystems and Cancelable Biometrics. EURASIP Journal on Information Security, 2011(3), 2011.

  7. C. Rathgeb, A. Uhl, and P. Wild. Reliability-balanced Feature Level Fusion for Fuzzy Commitment Scheme. In Proc. Int’l Joint Conf. on Biometrics, pages 1–7. IEEE, 2011.

    Google Scholar 

  8. C. Rathgeb, A. Uhl, and P. Wild. Shifting Score Fusion: On Exploiting Shifting Variation in Iris Recognition. In Proc. 26th ACM Symp. On Applied Computing, pages 1–5. ACM, 2011.

    Google Scholar 

  9. C. Rathgeb, A. Uhl, and P. Wild. Iris-Biometric Comparators: Exploiting Comparison Scores towards an Optimal Alignment under Gaussian Assumption. In Proc. 5th Int’l Conf. on Biometrics, pages 1–6. IEEE, 2012.

    Google Scholar 

  10. J. Zuo, N. K. Ratha, and J. H. Connel. Cancelable Iris Biometric. Proc. 19th Int’l Conf. on Pattern Recognition, pages 1–4, 2008.

    Google Scholar 

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Authors
  1. Christian Rathgeb
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Additional information

Christian Rathgeb is a postdoctoral researcher in the da/sec Biometrics and Internet Security Reasearch Group at the Center of Applied Security Research Darmstadt (CASED), Germany.

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Rathgeb, C. Towards enhancing the security and accuracy of iris recognition systems. Datenschutz Datensich 37, 367–370 (2013). https://doi.org/10.1007/s11623-013-0142-x

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  • DOI: https://doi.org/10.1007/s11623-013-0142-x

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