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A new approach to the design of hybrid finer directional wavelet filter bank for iris feature extraction and classification using k-out-of-n:A post-classifier

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Abstract

This paper presents a novel iris feature extraction scheme using two-dimensional non-separable, non-redundant, multi-scale hybrid finer directional wavelet filter bank and classification using fused post-classifier under non-ideal environmental conditions. The proposed approach overcomes limited directionality of wavelet transform. The designed filter bank converts the wavelet basis functions to a set of directional basis elements by employing the combination of designed bi-orthogonal wavelet filter bank and modified checkerboard-shaped filter bank (designed using triplet of half-band filters). The false rejection rate is reduced with the help of k-out-of-n:A rule. The proposed technique is capable to handle possible artifacts especially inaccurate iris localization, occlusion of eyelids, pupil, eyelashes, reflection on iris, non-linear deformation, head-tilt, etc. The performance of the proposed scheme is validated using CASIA-Iris V2.0, MMU1, and UBIRIS databases. Finally, the performance of proposed approach is compared with other existing iris recognition algorithms to demonstrate its potential.

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References

  1. Jain AK, Ross A, Pankanti S (2006) Biometrics: a tool for information security. IEEE Trans Inform Forensic Secur 1(2):125–143

    Article  Google Scholar 

  2. Jain AK, Ross A, Nandakumar K (2011) Introduction to biometrics. Springer, New York (ISBN 978-0-387-77325-4)

  3. Daugman JG (1993) High confidence of visual recognition of persons by a test of statistical independence. IEEE Trans Pattern Anal Machine Intell 15(11):1148–1161

    Article  Google Scholar 

  4. Proenca H, Alexandre LA (2007) Toward non-cooperative iris recognition: a classification approach using multiple signatures. IEEE Trans Pattern Anal Machine Intell 9(4):607–612

    Article  Google Scholar 

  5. Masek L (2003) Recognition of human iris pattern for biometric identification. M. Thesis, The University of Western Australia, Australia

  6. Vatsa M, Singh R, Noore A (2008) Improving iris recognition performance using segmentation, quality enhancement, match score fusion, and indexing. IEEE Trans Syst Man Cybern Part B Cybern 38(4):1021–1034

    Article  Google Scholar 

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

    Article  Google Scholar 

  8. Wildes RP (1997) Iris recognition: an emerging biometric technology. Proc IEEE 85(9):1348–1363

    Article  Google Scholar 

  9. Lim S, Lee K, Byeon O, Kim T (2001) Efficient iris recognition through improvement of feature vector and classifier. ETRI J 23(2):61–70

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

  12. Nabti M, Ghouti L, Bouridane A (2008) An effective and fast iris recognition system based on a combined multiscale feature extraction technique. Pattern Recogn 41:868–879

    Article  MATH  Google Scholar 

  13. Velisavljevic V (2009) Low-complexity iris coding and recognition based on directionlets. IEEE Trans Inform Forensics Secur 4(3):410–417

    Article  Google Scholar 

  14. Abhyankar A, Schuckers S (2010) A novel biorthogonal wavelet network system for off-angle iris recognition. Pattern Recogn 43:987–1007

    Article  MATH  Google Scholar 

  15. Park CH, Lee JJ, Oh SK, Song YC, Choi DH, Park KH (2003) Iris feature extraction and matching based on multiscale and directional image representation. In: Proceeding of the 4th international conference on scale space methods in computer vision, Isle of Skye, UK. Springer-Verlag, pp 576–583

  16. Monro DM, Rakshit S, Zhang D (2007) DCT-based iris recognition. IEEE Trans Pattern Anal Machine Intell 29(4):586–594

    Article  Google Scholar 

  17. Sun Z, Tan T (2009) Ordinal measures for iris recognition. IEEE Trans Pattern Anal Machine Intell 31(12):2211–2226

    Article  Google Scholar 

  18. Dong W, Tan T, Sun Z (2010) Iris matching based on personalized weight map. IEEE Trans Pattern Anal Machine Intell 99:1–14

    Google Scholar 

  19. Huang J, You X, Yuan Y, Yang F, Lin L (2010) Rotation invariant iris feature extraction using Gaussian Markov random fields with non-separable wavelet. Neurocomputing 73:883–894

    Article  Google Scholar 

  20. Al-Zubi RT, Abu-Al-Nadi DI (2007) Automated personal identification system based on human iris analysis. Pattern Anal Appl 10:147–164

    Article  MathSciNet  Google Scholar 

  21. Chou CT, Shih SW, Chen WS, Cheng VW, Chen DY (2010) Non-orthogonal view iris recognition system. IEEE Trans Circuits Syst Video Technol 20(3):417–430

    Article  Google Scholar 

  22. Opitz D, Maclin R (1999) Popular ensemble methods: an empirical study. J Artif Intell Res 11:169–198

    MATH  Google Scholar 

  23. Bowyer KW, Hollingworth K, Flynn PJ (2008) Image understanding for iris biometrics: a survey. Comput Vis Image Underst 110(2):281–307

    Article  Google Scholar 

  24. Patil BD, Patwardhan PG, Gadre VM (2008) On the design of FIR wavelet filter banks using factorization of a halfband polynomial. IEEE Signal Process Lett 15:485–488

    Article  Google Scholar 

  25. Ansari R, Kim CW, Dedovic M (1999) Structure and design of two-channel filter banks derived from a triplet of halfband filtres. IEEE Trans Circuits Syst II Analog Digit Signal Process 46(12):1487–1496

    Article  Google Scholar 

  26. Phoong SM, Kim CW, Vaidyanathan PP, Ansari R (1995) A new class of two-channel biorthogonal filter banks and wavelet bases. IEEE Trans Signal Process 43(3):649–665

    Article  Google Scholar 

  27. Eslami R, Radha H (2007) A new family of nonredundant transforms using hybrid wavelets and direcitonal filter banks. IEEE Trans Image Process 16(4):1152–1167

    Article  MathSciNet  Google Scholar 

  28. Lu Y, Do MN (2005) The finer directional wavelet transform. In: Proceeding of the IEEE international conference on acoustic, speech, and signal processing, Philadelphia

  29. Bamberger RH, Smith MJT (1992) A filter bank for the directional decomposition of images: theory and design. IEEE Trans Signal Process 40(4):882–893

    Article  Google Scholar 

  30. Kingsbury N (2001) Complex wavelets for shift invariant analysis and filtring of signals. J Appl Comput Harmon Anal 10(3):234–253

    Article  MATH  MathSciNet  Google Scholar 

  31. Kokare MB, Biswas PK, Chatterji BN (2005) Texture image retrieval using new rotated complex wavelet fitlers. IEEE Trans Syst Man Cybern Part B Cybern 35(6):1168–1178

    Article  Google Scholar 

  32. Smeraldi F, Bigun J (2002) Retinal vision applied to facial features detection and face authentication. Pattern Recogn Lett 23:463–475

    Article  MATH  Google Scholar 

  33. Alonso-Fernandez F, Bigun J(2012) Periocular recognition using retinotopic sampling and Gabor decomposition. http://rd.springer.com/chapter/10.1007/978-3-642-33868-7_31. Accessed 18 Jan 2013

  34. Vaidyanathan PP (1993) Multirate systems and filter banks. Prentice-Hall, Englewood Cliffs

    MATH  Google Scholar 

  35. Vetterli M, Kovacevic J (1995) Wavelets and subband coding. Prentice-Hall, Englewood Cliffs

    MATH  Google Scholar 

  36. Eslami R, Radha H (2010) Design of regular wavelets using a three-step ladder structure. IEEE Trans Signal Process 58(4):2088–2101

    Article  MathSciNet  Google Scholar 

  37. Tay DBH (2001) Balancced spatial and frequency localized 2-D non-separable wavelet filters. In: Proceeding of IEEE international symposium on circuits and systems, vol 2, pp 489–492

  38. Chen Y, Dass SC, Jain AK (2006) Localized iris image quality using 2-D wavelets. In: International conference on biometrics, pp 373–381

  39. Ross A, Jain AK (2003) Information fusion in biometrics. Pattern Recogn Lett 24(13):2115–2125

    Article  Google Scholar 

  40. Charles EE (1997) An introduction to reliability and maintability engineering. McGraw-Hill, London

    Google Scholar 

  41. CASIA-Iris V2 (2004) http://biometrics.idealtest/. Accessed 19 July 2007

  42. Multimedia university iris database (2006) http://pesona.mmu.edu.my/~ccteo/. Accessed 10 Aug 2007

  43. Proenca H, Alexandre LA (2005) UBIRIS: a noisy iris image database. http://iris.di.ubi.pt/. Accessed 18 Nov 2007

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Acknowledgments

The authors are very much thankful to the editor, associate editor, and anonymous reviewers for their constructive comments and valuable suggestions that helped to improve the quality of this manuscript significantly. The authors would like to thank Chinese Academy of Sciences’ Institute of Automation (CASIA), U.B.I (Portugal), and MMU1 for providing the iris databases used in this paper.

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Correspondence to Amol D. Rahulkar.

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Rahulkar, A.D., Waghmare, L.M. & Holambe, R.S. A new approach to the design of hybrid finer directional wavelet filter bank for iris feature extraction and classification using k-out-of-n:A post-classifier. Pattern Anal Applic 17, 529–547 (2014). https://doi.org/10.1007/s10044-013-0334-x

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