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Analysis of Particular Iris Recognition Stages

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Multimedia Communications, Services and Security (MCSS 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 149))

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Abstract

In this paper particular stages are analyzed present in the iris recognition process. First, we shortly describe available acquisition systems and databases of iris images, which can be used for tests. Next, we concentrate on features extraction and coding with the time analysis. Results of average time of loading the image, segmentation, normalization, features encoding, and also recognition accuracy for CASIA and IrisBath databases are presented.

This paper was prepared within the INDECT project.

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References

  1. Daugman, J.G.: High confidence visual recognition of persons by a test of statistical independence. IEEE Trans. Pattern Anal.Mach. Intell. 15(11), 1148–1161 (1993)

    Article  Google Scholar 

  2. Wildes, R.P.: Iris recognition: An emerging biometric technology. Proc. IEEE 85(9), 1348–1363 (1997)

    Article  Google Scholar 

  3. Boles, W.W., Boashash, B.: A human identification technique using images of the iris and wavelet transform. IEEE Trans. Signal Process 46(4), 1185–1188 (1998)

    Article  Google Scholar 

  4. Ma, L., Tan, T., Wang, Y., Zhang, D.: Personal identification based on iris texture analysis. IEEE Trans. Pattern Anal. Mach. Intell. 25(12), 1519–1533 (2003)

    Article  Google Scholar 

  5. Ma, L., Tan, T., Wang, Y., Zhang, D.: Efficient iris recognition by characterizing key local variations. IEEE Trans. Image Process 13(6), 739–750 (2004)

    Article  Google Scholar 

  6. Sanchez-Avila, C., Sanchez-Reillo, R.: Two different approaches for iris recognition using Gabor filters and multiscale zero-crossing representation. Pattern Recognit. 38(2), 231–240 (2005)

    Article  Google Scholar 

  7. Vatsa, M., Singh, R., Noore, A.: Reducing the false rejection rate of iris recognition using textural and topological features. Int. J. Signal Process 2(1), 66–72 (2005)

    Google Scholar 

  8. Yu, L., Zhang, D., Wang, K., Yang, W.: Coarse iris classification using box-counting to estimate fractal dimensions. Pattern Recognit. 38(11), 1791–1798 (2005)

    Article  Google Scholar 

  9. Monro, D.M., Rakshit, S., Zhang, D.: DCT-based iris recognition. IEEE Trans. Pattern Anal. Mach. Intell. 29(4), 586–596 (2007)

    Article  Google Scholar 

  10. Poursaberi, A., Araabi, B.N.: Iris recognition for partially occluded images: Methodology and sensitivity analysis. EURASIP J. Adv. Signal Process 2007(1) Article ID 36751, 20 (2007)

    Article  MATH  Google Scholar 

  11. Biometric data interchange formats – Part 6: Iris image data, ISO/IEC 19794-6 (2005)

    Google Scholar 

  12. Oki IRISPASS®-M, http://www.oki.com/en/press/2005/z05049e-2.html

  13. Panasonic Iris Reader BM-ET330, http://panasonic.co.jp/pss/bmet330/en/

  14. Chinese Academy of Sciences’ Institute of Automation, “CASIA-IrisV3”, http://www.cbsr.ia.ac.cn/IrisDatabase.htm and Biometric Ideal Test website http://biometrics.idealtest.org/

  15. Signal and Image Processing Group (SIPG), University of Bath Iris Image Database, http://www.bath.ac.uk/elec-eng/research/sipg/irisweb/

  16. Proença, H., et al.: The UBIRIS.v2: A Database of Visible Wavelength Iris Images Captured On-The-Move and At-ADistance. IEEE Transactions on Pattern Analysis and Machine Intelligence, Digital Object Identifier 10.1016/j.imavis.2009.03.003 (2009)

    Google Scholar 

  17. Dobeš, M., Machala, L.: Iris Database, http://www.inf.upol.cz/iris/

  18. Masek, L.: Recognition of Human Iris Patterns for Biometric Identification, M. Thesis, The University of Western Australia (2003)

    Google Scholar 

  19. Kaminski, T.: Implementacja i analiza skuteczności identyfikacji osób na podstawie tęczówki (Implementation and efficiency analysis of person identification using iris recognition), M.Sc. Thesis, Supervisor: Tomasz Marciniak, Poznan University of Technology (2007)

    Google Scholar 

  20. Kovesi, P.: Some of my MATLAB functions, http://www.csse.uwa.edu.au/~pk/

  21. Poursaberi, A., Araabi, B.N.: A Half-Eye Wavelet Based Method for Iris Recognition. In: Proceedings of the ISDA (2005)

    Google Scholar 

  22. Pereira, M.B., Paschoarelli Veiga, A.C.: A method for improving the reliability of an iris recognition system, Department of Electrical Engineering – Federal University of Uberlandia(UFU) – Brazil (2005)

    Google Scholar 

  23. Field, D.: Relations between the statistics of natural images and the response properties of cortical cells. Journal of the Optical Society of America (1987)

    Google Scholar 

  24. Dąbrowski, A., et al.: D7.3 – Biometric features analysis component based on video and image information. INDECT Project FP7-218086 (2010)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Chair of Control and System Engineering, Division of Signal Processing and Electronic Systems, Poznań University of Technology, ul. Piotrowo 3a, 60-965, Poznań, Poland

    Tomasz Marciniak, Adam Dąbrowski, Agata Chmielewska & Agnieszka Krzykowska

Authors
  1. Tomasz Marciniak
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  2. Adam Dąbrowski
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  3. Agata Chmielewska
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  4. Agnieszka Krzykowska
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Editor information

Editors and Affiliations

  1. Department of Telecommunications, AGH University of Science and Technology, al. Mickiewicza 30, 30-059, Krakow, Poland

    Andrzej Dziech

  2. Multimedia Systems Department, Gdansk University of Technology, Narutowicza 11/22, 80-233, Gdansk, Poland

    Andrzej Czyżewski

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Marciniak, T., Dąbrowski, A., Chmielewska, A., Krzykowska, A. (2011). Analysis of Particular Iris Recognition Stages. In: Dziech, A., Czyżewski, A. (eds) Multimedia Communications, Services and Security. MCSS 2011. Communications in Computer and Information Science, vol 149. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21512-4_24

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  • DOI: https://doi.org/10.1007/978-3-642-21512-4_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21511-7

  • Online ISBN: 978-3-642-21512-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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