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A Multi-algorithmic Colour Iris Recognition System

  • Conference paper
Soft Computing Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 195))

Abstract

The reported accuracies of iris recognition systems are generally higher on near infrared images than on colour RGB images. To increase a colour iris recognition system’s performance, a possible solution is a multialgorithmic approach with an appropriate fusion mechanism. In the present work, this approach is investigated by fusing three algorithms at the score level to enhance the performance of a colour iris recognition system. The contribution of this paper consists of proposing 2 novel feature extraction methods for colour iris images, one based on a 3-bit encoder of the 8 neighborhood and the other one based on gray level co-occurrence matrix. The third algorithm employed uses the classical Gabor filters and phase encoding for feature extraction. A weighted average is used as a matching score fusion. The efficiency of the proposed iris recognition system is demonstrated on UBIRISv1 dataset.

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References

  1. Daugman, J.G.: High confidence visual recognition of persons by a test of statistical independence. IEEE Transactions on Pattern Analysis and Machine Intelligence 15(11), 1148–1161 (1993)

    Article  Google Scholar 

  2. Ma, L., Wang, Y.H., Tan, T.N.: Iris recognition using circular symmetric filters. In: Kasturi, R., Laurendeau, D., Suen, C. (eds.) Proceedings of 16th International Conference on Pattern Recognition, vol. II, pp. 414–417. IEEE Computer Soc., Los Alamitos (2002)

    Google Scholar 

  3. Ma, L., Tan, T.N., Wang, Y.H., Zhang, D.X.: Efficient iris recognition by characterizing key local variations. IEEE Transactions on Image Processing 13(6), 739–750 (2004)

    Article  Google Scholar 

  4. NIST. National Institute of Standards and Technology (2010), http://www.nist.gov (cited June 30, 2012)

  5. Grother, P., Tabassi, E., Quinn, G.W., Salamon, W.: IREX 1 Report - Performance of Iris Recognition Algorithms on Standard Images (2009)

    Google Scholar 

  6. Standardization, I.O. f. ISO/IEC 19794-6:2011 (2011), http://www.iso.org/iso/iso_catalogue/catalogue_tc/catalogue_detail.htm?csnumber=50868 (cited May 30, 2012)

  7. Proenca, H., Alexandre, L.A.: Toward Covert Iris Biometric Recognition: Experimental Results From the NICE Contests. IEEE Transactions on Information Forensics and Security 7(2), 798–808 (2012)

    Article  Google Scholar 

  8. Proenca, H., et al.: The UBIRIS.v2: A Database of Visible Wavelength Iris Images Captured On-the-Move and At-a-Distance. IEEE Transactions on Pattern Analysis and Machine Intelligence 32(8), 1529–1535 (2010)

    Article  Google Scholar 

  9. Radu, P., Sirlantzis, K., Howells, W.G.J., Deravi, F., Hoque, S.: Information Fusion for Unconstrained Iris Recognition. International Journal of Hybrid Information Technology 4(4), 1–12 (2011)

    Google Scholar 

  10. Radu, P., Sirlantzis, K., Howells, W.G.J., Hoque, S., Deravi, F.: A Versatile Iris Segmentation Algorithm. In: Arslan Bromme, C.B. (ed.) BIOSIG 2011. Kollen Druck+Vwrlag, Darmstadt, pp. 137–151 (2011)

    Google Scholar 

  11. Proença, H., Alexandre, L.A.: UBIRIS: A Noisy Iris Image Database. In: Roli, F., Vitulano, S. (eds.) ICIAP 2005. LNCS, vol. 3617, pp. 970–977. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  12. Vatsa, M., Singh, R., Noore, A.: Improving iris recognition performance using segmentation, quality enhancement, match score fusion, and indexing. IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics 38(4), 1021–1035 (2008)

    Article  Google Scholar 

  13. Nixon, M.S., Aguado, A.S.: Feature Extraction and Image Processing, ed. Newnes 2002: Newness

    Google Scholar 

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

    Article  Google Scholar 

  15. Balas, V.E., Motoc, I.M., Barbulescu, A.: Combined Haar-Hilbert and Log-Gabor Based Iris Encoders. In: Balas, V.E., Fodor, J., Varkonyi-Koczy, A. (eds.) New Concepts and Applications in Soft Computing. Studies in Computational Intelligence, vol. 417, pp. 1–26. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  16. Popescu-Bodorin, N., Balas, V.E.: Comparing Haar-Hilbert and Log-Gabor based iris encoders on Bath Iris Image Database. In: 2010 4th International Workshop on Soft Computing Applications, SOFA (2010)

    Google Scholar 

  17. Hosseini, M.S., Araabi, B.N., Soltanian-Zadeh, H.: Pigment Melanin: Pattern for Iris Recognition. IEEE Transactions on Instrumentation and Measurement 59(4), 792–804 (2010)

    Article  Google Scholar 

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Authors and Affiliations

  1. School of Engineering and Digital Arts, University of Kent, Canterbury, U.K

    Petru Radu, Konstantinos Sirlantzis, Gareth Howells, Sanaul Hoque & Farzin Deravi

Authors
  1. Petru Radu
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  2. Konstantinos Sirlantzis
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  3. Gareth Howells
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  4. Sanaul Hoque
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  5. Farzin Deravi
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Corresponding author

Correspondence to Petru Radu .

Editor information

Editors and Affiliations

  1. , Department of Automation & Applied Infor, Aurel Vlaicu University of Arad, Blvd. Revolutiei 77, Arad, 310130, Romania

    Valentina Emilia Balas

  2. , Institute of Intelligent Engineering, Óbuda University, Bécsi út 96/b, Budapest, 1034, Hungary

    János Fodor

  3. Dept. Measurement &, Information Systems, Technical University Budapest, Magyar tudósok körutja 2, Budapest, 1521, Hungary

    Annamária R. Várkonyi-Kóczy

  4. , Department of Informatics, University of Szeged, Arpad ter 2., Szeged, 6720, Hungary

    Joszef Dombi

  5. , School of Electrical and Information, University of South Australia, 5095, Adelaide, Australia

    Lakhmi C. Jain

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Radu, P., Sirlantzis, K., Howells, G., Hoque, S., Deravi, F. (2013). A Multi-algorithmic Colour Iris Recognition System. In: Balas, V., Fodor, J., Várkonyi-Kóczy, A., Dombi, J., Jain, L. (eds) Soft Computing Applications. Advances in Intelligent Systems and Computing, vol 195. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33941-7_7

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  • DOI: https://doi.org/10.1007/978-3-642-33941-7_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33940-0

  • Online ISBN: 978-3-642-33941-7

  • eBook Packages: EngineeringEngineering (R0)

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