Skip to main content
SpringerLink
Log in

A Survey of Iris Biometrics Research: 2008–2010

  • Chapter
  • First Online:
Handbook of Iris Recognition

Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

Abstract

A recent survey of iris biometric research from its inception through 2007, roughly 15 years of research, lists approximately 180 publications. This new survey is intended to update the previous one, and covers iris biometrics research over the period of roughly 2008–2010. Research in iris biometrics has expanded so much that, although covering only 3 years and intentionally being selective about coverage, this new survey lists a larger number of references than the inception-through-2007 survey.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Adam, M., Rossant, F., Mikovicova, B., Amiel, F.: Iris identification based on a local analysis of the iris texture. In: Proceedings of 6th International Symposium on Image and Signal Processing and Analysis (ISPA), pp. 523–528 (2009)

    Google Scholar 

  2. Adjedj, M., Bringer, J., Chabanne, H., Kindarji, B.: Biometric identification over encrypted data made feasible. In: Information Systems Security: Lecture Notes in Computer Science #5905, pp. 86–100 (2009)

    Google Scholar 

  3. Agrawal, N., Savvides, M.: Biometric data hiding: A 3 factor authentication approach to verify identity with a single image using steganography, encryption and matching. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR Workshops), pp. 85–92 (2009)

    Google Scholar 

  4. Al-Qunaieer, F.S., Ghouti, L.: Color iris recognition using hypercomplex gabor wavelets. In: Symposium on Bio-Inspired Learning and Intelligent Systems for Security (BLISS ’09), pp. 18–19 (2009)

    Google Scholar 

  5. Alghamdi, A.S., Ullah, H., Mahmud, M., Khan, M.K.: Bio-chaotic stream cipher-based iris image encryption. In: International Conference on Computational Science and Engineering (CSE ’09), pp. 739–744 (2009)

    Google Scholar 

  6. Baig, A., Bouridane, A., Kurugollu, F., Qu, G.: Fingerprint-iris fusion based identification system using a single hamming distance. In: Symposium on Bio-inspired Learning and Intelligent Systems for Security (BLISS ’09), pp. 9–12 (2009)

    Google Scholar 

  7. Baker, S., Bowyer, K., Flynn, P.: Empirical evidence for correct iris match score degradation with increased time-lapse between gallery and probe matches. In: Advances in Biometrics: Lecture Notes in Computer Science #5558, pp. 1170–1179 (2009)

    Google Scholar 

  8. Baker, S., Hentz, A., Bowyer, K., Flynn, P.: Degradation of iris recognition performance due to non-cosmetic prescription contact lenses. Comput. Vis. Image Underst. 114, 1030–1044 (2010)

    Article  Google Scholar 

  9. Bastys, A., Kranauskas, J., Masiulis, R.: Iris matching by local extremum points of multiscale taylor expansion. In: Advances in Biometrics: Lecture Notes in Computer Science #5558, pp. 1070–1079 (2009)

    Google Scholar 

  10. Belcher, C., Du, Y.: A selective feature information approach for iris image-quality measure. IEEE Trans. Inf. Forensics Secur. 3(3), 572–577 (2008)

    Article  Google Scholar 

  11. Bharadwaj, H., Bhatt, H.S., Vatsa, M., Singh, R.: Periocular biometrics: when iris recognition fails. In: Fourth IEEE International Conference on Biometrics: Theory Applications and Systems (BTAS 10) (2010)

    Google Scholar 

  12. Bhatnagar, J.R., Patney, R.K., Lall, B.: An information theoretic approach for formulating probability of random correspondence of biometrics. In: World Congress on Nature and Biologically Inspired Computing (NaBIC), pp. 1184–1189 (2009)

    Google Scholar 

  13. Bhattacharjee, A., Saggi, M., Tayal, R.B.A., Kumar, A.: Decision theory based multimodal biometric authentication system using wavelet transform. 2009 International Conference on Machine Learning and Cybernetics, vol. 4, pp. 2336–2342 (2009)

    Google Scholar 

  14. Bhattacharyya, D., Ranjan, R., Das, P., Kim, T., Bandyopadhyay, S.K.: Biometric authentication techniques and its future possibilities. In: Second International Conference on Computer and Electrical Engineering (ICCEE ’09), vol. 2, pp. 652–655 (2009)

    Google Scholar 

  15. Biosecure: A biometric reference system for iris OSIRIS version 2.01 (2009)

    Google Scholar 

  16. Bodade, R.M., Talbar, S.N.: Dynamic iris localisation: a novel approach suitable for fake iris detection. In: International Conference on Ultra Modern Telecommunications and Workshops (ICUMT ’09), pp. 1–5 (2009)

    Google Scholar 

  17. Bodade, R.M., Talbar, S.N.: Shift invariant iris feature extraction using rotated complex wavelet and complex wavelet for iris recognition system. In: Seventh International Conference on Advances in Pattern Recognition (ICAPR ’09), pp. 449–452 (2009)

    Google Scholar 

  18. Boddeti, V.N., Kumar, B.V.K.V.: Extended-depth-of-field iris recognition using unrestored wavefront-coded imagery. IEEE Trans. Syst. Man Cybern. 40(3), 495–508 (2010)

    Article  Google Scholar 

  19. Borgen, H., Bours, P., Wolthusen, S.: Simulating the influences of aging and ocular disease on biometric recognition performance. In: Advances in Biometrics: Lecture Notes in Computer Science #5558, pp. 857–867 (2009)

    Google Scholar 

  20. Bowyer, K.W., Flynn, P.J.: The ND-IRIS-0405 Iris Image Database

    Google Scholar 

  21. Bowyer, K.W., Hollingsworth, K., Flynn, P.: Image understanding for iris biometrics: a survey. Comput. Vis. Image Underst. 110(2), 281–307 (2008)

    Article  Google Scholar 

  22. Bowyer, K.W., Baker, S., Hentz, A., Hollingsworth, K., Peters, T., Flynn, P.: Factors that degrade the match distribution in iris biometrics. Identity Inf. Soc. 2, 327–343 (2009)

    Article  Google Scholar 

  23. Breitenbach, L., Chawdhry, P.: Image quality assessment and performance evaluation for multimodal biometric recognition using face and iris. In: Proceedings of 6th International Symposium on Image and Signal Processing and Analysis (ISPA), pp. 550–555 (2009)

    Google Scholar 

  24. Broussard, R.P., Ives, R.W.: Using artificial neural networks and feature saliency to identify iris measurements that contain the most discriminatory information for iris segmentation. In: IEEE Workshop on Computational Intelligence in Biometrics: Theory, Algorithms, and Applications (CIB), pp. 46–51 (2009)

    Google Scholar 

  25. Campos, S., Salas, R., Allende, H., Castro, C.: Multimodal algorithm for iris recognition with local topological descriptors. In: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: Lecture Notes in Computer Science #5856, pp. 766–773 (2009)

    Google Scholar 

  26. Carneiro, M., Veiga, A., Silva, S.P., Flores, E.L., Carrijo, G.A.: Analyzing the performance of algorithms used to localize the iris region in eye images submitted to severely compressed images. In: IEEE International Symposium on Intelligent Signal Processing (WISP), pp. 281–285 (2009)

    Google Scholar 

  27. Chen, R., Lin, X., Ding, T., Ma, J.: Accurate and fast iris segmentation applied to portable image capture device. In: IEEE International Workshop on Imaging Systems and Techniques (IST ’09), pp. 80–84 (2009)

    Google Scholar 

  28. Chen, W., Huang, R., Hsieh, L.: Iris recognition using 3D co-occurrence matrix. In: Advances in Biometrics: Lecture Notes in Computer Science #5558, pp. 1122–1131 (2009)

    Google Scholar 

  29. Chen, W.S., Chuan, C.A., Shih, S.W., Chang, S.H.: Iris recognition using 2D-LDA + 2D-PCA. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 869–872 (2009)

    Google Scholar 

  30. Chen, Y., Adjouadi, M., Barreto, A., Rishe, N., Andrian, J.: A computational efficient iris extraction approach in unconstrained environments. In: IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems (BTAS 09), pp. 1–7 (2009)

    Google Scholar 

  31. Chen, Y., Adjouadi, M., Changan, H., Barreto, A.: A new unconstrained iris image analysis and segmentation method in biometrics. In: IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI ’09), pp. 13–16 (2009)

    Google Scholar 

  32. Chou, C.T., Shih, S.W., Chen, W.S., Cheng, V.W., Chen, D.Y.: Non-orthogonal view iris recognition system. In: IEEE Trans. Circuits Syst. Video Technol. 20(3), 417–430 (2010)

    Article  Google Scholar 

  33. Chowhan, S.S., Shinde, G.N.: Evaluation of statistical feature encoding techniques on iris images. In: 2009 WRI World Congress on Computer Science and Information Engineering, vol. 7, pp. 71–75 (2009)

    Google Scholar 

  34. Conti, V., Milici, G., Ribino, P., F. Sorbello, a.S.V.: Fuzzy fusion in multimodal biometric systems. In: KES 2007/WIRN 2007: Lecture Notes in Artificial Intelligence #4692, pp. 108–115 (2007)

    Google Scholar 

  35. Daugman, J.: Iris recognition and anti-spoofing countermeasures. In: 7th International Biometrics Conference, London (2004)

    Google Scholar 

  36. Daugman, J., Downing, C.: Effect of severe image compression on iris recognition performance. IEEE Trans. Inf. Forensics Secur. 3(1), 52–61 (2008)

    Article  Google Scholar 

  37. Dong, W., Sun, Z., Tan, T.: A design of iris recognition system at a distance. In: Chinese Conference on Pattern Recognition (CCPR), pp. 1–5 (2009)

    Google Scholar 

  38. Dong, W., Tan, T., Sun, Z.: Iris matching based on personalized weight map. IEEE Trans. Pattern Anal. Mach. Intell. 33(9), 1744–1757 (2011)

    Article  Google Scholar 

  39. Dozier, G., Frederiksen, K., Meeks, R.: Minimizing the number of bits needed for iris recognition via bit inconsistency and GRIT. In: IEEE Workshop on Computational Intelligence in Biometrics: Theory, Algorithms, and Applications, (CIB), pp. 30–37 (2009)

    Google Scholar 

  40. Dutta, M., Gupta, P., Pathak, V.: Biometric based unique key generation for authentic audio watermarking. In: Pattern Recognition and Machine Intelligence: Lecture Notes in Computer Science #5909, pp. 458–463 (2009)

    Google Scholar 

  41. Dutta, M.K., Gupta, P., Pathak, V.K.: Biometric based watermarking in audio signals. In: International Conference on Multimedia Information Networking and Security (MINES 2009), vol. 1, pp. 10–14 (2009)

    Google Scholar 

  42. Dutta, M.K., Gupta, P., Pathak, V.K.: Blind watermarking in audio signals using biometric features in wavelet domain. In: IEEE Region 10 Conference (TENCON), pp. 1–5 (2009)

    Google Scholar 

  43. Du, Y., Thomas, N.L., Arslanturk, E.: Multi-level iris video image thresholding. In: IEEE Workshop on Computational Intelligence in Biometrics: Theory, Algorithms, and Applications, (CIB), pp. 38–45 (2009)

    Google Scholar 

  44. Du, Y., Arslanturk, E., Zhou, Z., Belcher, C.: Video-based noncooperative iris image segmentation. IEEE Trans. Syst. Man Cybern. 41(1), 64–74 (2011)

    Article  Google Scholar 

  45. Elmadani, A.B.: Human authentication using fingeriris algorithm based on statistical approach. In: Second International Conference on Networked Digital Technologies (NDT 2010), pp. 288–296 (2010)

    Google Scholar 

  46. Erbilek, M., Toygar, O.: Recognizing partially occluded irises using subpattern-based approaches. In: 24th International Symposium on Computer and Information Sciences (ISCIS), pp. 606–610 (2009)

    Google Scholar 

  47. Eskandari, M., Toygar, O.: Effect of eyelid and eyelash occlusions on iris images using subpattern-based approaches. In: Fifth International Conference on Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control, (ICSCCW), pp. 1–4 (2009)

    Google Scholar 

  48. Färberböck, P., Hämmerle-Uhl, J., Kaaser, D., Pschernig, E., Uhl, A.: Transforming rectangular and polar iris images to enable cancelable biometrics. In: Image Analysis and Recognition: Lecture Notes in Computer Science #6112, pp. 276–286 (2010)

    Google Scholar 

  49. Fatt, R., Haur, T.Y., Mok, K.M.: Iris verification algorithm based on texture analysis and its implementation on dsp. In: International Conference on Signal Acquisition and Processing (ICSAP), pp. 198–202 (2009)

    Google Scholar 

  50. Fatt, R.Y., Tay, Y.H., Mok, K.M.: DSP-based implementation and optimization of an iris verification algorithm using textural feature. In: Sixth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), vol. 5, pp. 374–378 (2009)

    Google Scholar 

  51. Fierrez, J., Galbally, J., Ortega-Garcia, J.: BiosecurID: a multimodal biometric database. Pattern Anal. Appl. 13, 235–246 (2010)

    Article  MathSciNet  Google Scholar 

  52. Gan, J.Y., Liu, J.F.: Fusion and recognition of face and iris feature based on wavelet feature and KFDA. In: International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR), pp. 47–50 (2009)

    Google Scholar 

  53. Garg, R., Gupta, V., Agrawal, V.: Efficient iris recognition method for identification. In: International Conference on Ultra Modern Telecommunications and Workshops, (ICUMT), pp. 1–6 (2009)

    Google Scholar 

  54. Garg, R., Shriram, N., Gupta, V., Agrawal, V.: A biometric security based electronic gadget control using hand gestures. In: International Conference on Ultra Modern Telecommunications and Workshops (ICUMT ’09), pp. 1–8 (2009)

    Google Scholar 

  55. Gentile, J.E., Ratha, N., Connell, J.: An efficient, two-stage iris recognition system. In: IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems (BTAS 09) (2009)

    Google Scholar 

  56. Gentile, J.E., Ratha, N., Connell, J.: SLIC: Short-length iris codes. In: IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems (BTAS) (2009)

    Google Scholar 

  57. Ghouti, L., Al-Qunaieer, F.S.: Color iris recognition using quaternion phase correlation. In: Symposium on Bio-inspired Learning and Intelligent Systems for Security (BLISS ’09), pp. 20–25 (2009)

    Google Scholar 

  58. Gonzaga, A., da Costa, R.M.: Extraction and selection of dynamic features of the human iris. In: XXII Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI), pp. 202–208 (2009)

    Google Scholar 

  59. Gorodnichy, D.O.: Evolution and evaluation of biometric systems. In: IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA), pp. 1–8 (2009)

    Google Scholar 

  60. Gorodnichy, D.O., Hoshino, R.: Score calibration for optimal biometric identification. In: Advances in Artificial Intelligence: Lecture Notes in Computer Science #6085, pp. 357–361 (2010)

    Google Scholar 

  61. Grabowski, K., Sankowski, W., Zubert, M., Napieralska, M.: Iris structure acquisition method. In: 16th International Conference Mixed Design of Integrated Circuits and Systems (MIXDES), pp. 640–643 (2009)

    Google Scholar 

  62. Grother, P., Tabassi, E., Quinn, G.W., Salamon, W.: Irex i: performance of iris recognition algorithms on standard images. In: NIST Interagency Report 7629 (2009)

    Google Scholar 

  63. Hämmerle-Uhl, J., Pschernig, E., Uhl, A.: Cancelable iris biometrics using block re-mapping and image warping. In: Information Security: Lecture Notes in Computer Science #5735, pp. 135–142 (2009)

    Google Scholar 

  64. Hämmerle-Uhl, J., Prähauser, C., Starzacher, T., Uhl, A.: Improving compressed iris recognition accuracy using JPEG2000 RoI coding. In: Advances in Biometrics: Lecture Notes in Computer Science #5558, pp. 1102–1111 (2009)

    Google Scholar 

  65. Hao, F., Anderson, R., Daugman, J.: Combining crypto with biometrics effectively. IEEE Trans. Comput. 55(9), 1081–1088 (2006)

    Article  Google Scholar 

  66. Hao, F., Daugman, J., Zielinski, P.: A fast search algorithm for a large fuzzy database. IEEE Trans. Inf. Forensics Secur. 3(2), 203–212 (2008)

    Article  Google Scholar 

  67. Haralick, R., Shanmugam, K., Dinstein, L.: Textural features for image classification. IEEE Trans. Syst. Man Cybern. 3(6), 610–621 (1973)

    Article  Google Scholar 

  68. Hassanien, A., Abraham, A., Grosan, C.: Spiking neural network and wavelets for hiding iris data in digital images. Soft Comput. 13(4), 401–416 (2009)

    Article  Google Scholar 

  69. He, X., An, X., Shi, P.: Statistical texture analysis based approach for fake iris detection using support vector machine. In: Advances in Biometrics: Lecture Notes in Computer Science #4642, pp. 540–546 (2007)

    Google Scholar 

  70. He, X., Yan, J., Chen, G., Shi, P.: Contactless autofeedback iris capture design. IEEE Trans. Instrum. Meas. 57(7), 1369–1375 (2008)

    Article  Google Scholar 

  71. He, Y., H. Yang, Y.H., He, H.: An elimination method of light spot based on iris image fusion. Commun. Comput. Inf. Sci. 15(12), 415–422 (2008)

    Google Scholar 

  72. He, Z., Sun, Z., Tan, T., Qiu, X.: Enhanced usability of iris recognition via efficient user interface and iris image restoration. In: 15th IEEE International Conference on Image Processing (ICIP), pp. 261–264 (2008)

    Google Scholar 

  73. He, X., Lu, Y., Shi, P.: A new fake iris detection method. In: Advances in Biometrics: Lecture Notes in Computer Science #5558, pp. 1132–1139 (2009)

    Google Scholar 

  74. He, Z., Sun, Z., Tan, T., Wei, Z.: Efficient iris spoof detection via boosted local binary patterns. In: Advances in Biometrics: Lecture Notes in Computer Science #5558, pp. 1080–1090 (2009)

    Google Scholar 

  75. He, Z., Tan, T., Sun, Z., Qiu, X.: Toward accurate and fast iris segmentation for iris biometrics. IEEE Trans. Pattern Anal. Mach. Intell. 31(9), 1670–1684 (2009)

    Article  Google Scholar 

  76. Hollingsworth, K., Bowyer, K., Flynn, P.: Pupil dilation degrades iris biometric performance. Comput. Vis. Image Underst. 113, 150–157 (2009)

    Article  Google Scholar 

  77. Hollingsworth, K.P., Bowyer, K.W., Flynn, P.J.: Pupil dilation degrades iris biometric performance. Comput. Vis. Image Underst. 113(1), 150–157 (2009)

    Article  Google Scholar 

  78. Hollingsworth, K.P., Bowyer, K.W., Flynn, P.J.: The best bits in an iris code. IEEE Trans. Pattern Anal. Mach. Intell. 31(6), 964–973 (2009)

    Article  Google Scholar 

  79. Hollingsworth, K.P., Bowyer, K.W., Flynn, P.J.: Using fragile bit coincidence to improve iris recognition. In: IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems (BTAS), pp. 1–6 (2009)

    Google Scholar 

  80. Hollingsworth, K., Peters, T., Bowyer, K.W., Flynn, P.J.: Iris recognition using signal-level fusion of frames from video. IEEE Trans. Inf. Forensics Secur. 4(4), 837–848 (2009)

    Article  Google Scholar 

  81. Hollingsworth, K.P., Bowyer, K.W., Flynn, P.J.: Identifying useful features for recognition in near-infrared periocular images. In: Fourth IEEE International Conference on Biometrics: Theory Applications and Systems (BTAS) (2010)

    Google Scholar 

  82. Huang, X., Ren, L., Yang, R.: Image deblurring for less intrusive iris capture. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1558–1565 (2009)

    Google Scholar 

  83. Ives, R.W., Bishop, D.A.D., Du, Y., Belcher, C.: Effects of image compression on iris recognition performance and image quality. In: IEEE Workshop on Computational Intelligence in Biometrics: Theory, Algorithms, and Applications (CIB), pp. 16–21 (2009)

    Google Scholar 

  84. Jang, Y., Kang, B.J., Park, K.R.: A novel portable iris recognition system and usability evaluation. Int. J. Control Autom. Syst. 8(1), 91–98 (2010)

    Article  Google Scholar 

  85. Johnson, P.A., Lopez-Meyer, P., Sazonova, N., Hua, F., Schuckers, S.: Quality in face and iris research ensemble (Q-FIRE). In: Fourth IEEE International Conference on Biometrics: Theory Applications and Systems (BTAS) (2010)

    Google Scholar 

  86. Kalka, N., Bartlow, N., Cukic, B.: An automated method for predicting iris segmentation failures. In: IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems (BTAS), pp. 1–8 (2009)

    Google Scholar 

  87. Kalka, N., Zuo, J., Schmid, N.A., Cukic, B.: Estimating and fusing quality factors for iris biometrics images. IEEE Trans. Syst. Man Cybern. 40(3), 509–524 (2010)

    Article  Google Scholar 

  88. Kanade, S., Petrovska-Delacretaz, D., Dorizzi, B.: Cancelable iris biometrics and using error correcting codes to reduce variability in biometric data. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 120–127 (2009)

    Google Scholar 

  89. Kanade, S., Petrovska-Delacretaz, D., Dorizzi, B.: Multi-biometrics based cryptographic key regeneration scheme. In: IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems (BTAS) (2009)

    Google Scholar 

  90. Kang, B.J., Park, K.R.: A new multi-unit iris authentication based on quality assessment and score level fusion for mobile phones. Mach. Vis. Appl. 21, 541–553 (2010)

    Article  Google Scholar 

  91. Kannavara, R., Bourbakis, N.: Iris biometric authentication based on local global graphs: an FPGA implementation. In: IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA), pp. 1–7 (2009)

    Google Scholar 

  92. Kheirolahy, R., Ebrahimnezhad, H., Sedaaghi, M.H.: Robust pupil boundary detection by optimized color mapping for iris recognition. In: 14th International CSI Computer Conference (CSICC), pp. 170–175 (2009)

    Google Scholar 

  93. Kong, A., Zhang, D., Kamel, M.: An analysis of IrisCode. IEEE Trans. Image Process. 19, 522–532 (2010)

    Article  MathSciNet  Google Scholar 

  94. Konrad, M., Stogner, H., Uhl, A.: Custom design of JPEG quantisation tables for compressing iris polar images to improve recognition accuracy. In: Advances in Biometrics: Lecture Notes in Computer Science #5558, pp. 1091–1101 (2009)

    Google Scholar 

  95. Konrad, M., Stogner, H., Uhl, A.: Evolutionary optimization of JPEG quantization tables for compressing iris polar images in iris recognition systems. In: Proceedings of 6th International Symposium on Image and Signal Processing and Analysis (ISPA), pp. 534–539 (2009)

    Google Scholar 

  96. Kostmajer, G., Stogner, H., Uhl, A.: Custom JPEG quantization for improved iris recognition accuracy. In: Emerging Challenges for Security, Privacy and Trust: IFIP Advances in Information and Communication Technology #297, pp. 76–86 (2009)

    Google Scholar 

  97. Krichen, E., Garcia-Salicetti, S., Dorizzi, B.: A new phase-correlation-based iris matching for degraded images. IEEE Trans. Syst. Man Cybern. 39(4), 924–934 (2009)

    Google Scholar 

  98. Krichen, E., Dorizzi, B., Sun, Z., Garcia-Salicetti, S.: Iris recognition. In: Guide to Biometric Reference Systems and Performance Evaluation, p. 25. Springer (2009)

    Google Scholar 

  99. Kyaw, K.S.S.: Iris recognition system using statistical features for biometric identification. In: International Conference on Electronic Computer Technology, pp.  554–556 (2009)

    Google Scholar 

  100. Labati, R.D., Piuri, V., Scotti, F.: Agent-based image iris segmentation and multiple views boundary refining. In: IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems (BTAS), pp. 1–7 (2009)

    Google Scholar 

  101. Labati, R.D., Piuri, V., Scotti, F.: Neural-based iterative approach for iris detection in iris recognition systems. In: IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA), pp. 1–6 (2009)

    Google Scholar 

  102. Laboratories, A.C.: The database of faces

    Google Scholar 

  103. Lee, Y., Phillips, P., Micheals, R.: An automated video-based system for iris recognition. In: Advances in Biometrics: Lecture Notes in Computer Science #5558, pp. 1160–1169 (2009)

    Google Scholar 

  104. Leonard, D.C., Pons, A.P., Asfour, S.S.: Realization of a universal patient identifier for electronic medical records through biometric technology. IEEE Trans. Inf. Technol. Biomed. 13(4), 494–500 (2009)

    Article  Google Scholar 

  105. Li, Y., Du, S.: Biometric watermarking based on affine parameters estimation. In: 2nd International Congress on Image and Signal Processing (CISP), pp. 1–6 (2009)

    Google Scholar 

  106. Li, Y., Du., S.: Biometric watermarking based on affine parameters estimation. In: International Conference on Multimedia Computing and Systems (ICMCS), pp. 123–128 (2009)

    Google Scholar 

  107. Li, Y., Savvides, M.: Automatic iris mask refinement for high performance iris recognition. In: IEEE Workshop on Computational Intelligence in Biometrics: Theory, Algorithms, and Applications (CIB), pp. 52–58 (2009)

    Google Scholar 

  108. Li, Y., Savvides, M.: A pixel-wise, learning-based approach for occlusion estimation of iris images in polar domain. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1357–1360 (2009)

    Google Scholar 

  109. Lin, J., Li, J.P., Lin, H., Ming, J.: Robust person identification with face and iris by modified PUM method. In: International Conference on Apperceiving Computing and Intelligence Analysis (ICACIA), pp. 321–324 (2009)

    Google Scholar 

  110. Liu, L., Gu, X.F., Li, J.P., Lin, J., Shi, J.X., Huang, Y.Y.: Research on data fusion of multiple biometric features. In: International Conference on Apperceiving Computing and Intelligence Analysis (ICACIA), pp. 112–115 (2009)

    Google Scholar 

  111. Liu, X., Li, P., Song, Q.: Eyelid localization in iris images captured in less constrained environment. In: Advances in Biometrics: Lecture Notes in Computer Science #5558, pp. 1140–1149 (2009)

    Google Scholar 

  112. Liu-Jimenez, J., Sanchez-Reillo, R., Fernandez-Saavedra, B.: Iris biometrics for embedded systems. IEEE Trans. Very Large Scale Integr. Syst. 19(2), 274–282 (2011)

    Article  Google Scholar 

  113. Luo, Y., Cheung, S., Ye, S.: Anonymous biometric access control based on homomorphic encryption. In: IEEE International Conference on Multimedia and Expo (ICME), pp. 1046–1049 (2009)

    Google Scholar 

  114. Lyle, J.R., Miller, P.E., Pundlik, S.J., Woodard, D.L.: Soft biometric classification using periocular region features. In: Fourth IEEE International Conference on iometrics: Theory Applications and Systems (BTAS) (2010)

    Google Scholar 

  115. Mahmud, M., Khan, M.K., Alghathbar, K.: Biometric-gaussian-stream (BGS) cipher with new aspect of image encryption (data hiding). In: Bio-Science and Bio-Technology, pp. 97–107. Springer, Berlin/Heidelberg (2009)

    Google Scholar 

  116. Maltoni, D.: Biometric fusion. In: Handbook of Fingerprint Recognition. Springer (2009)

    Google Scholar 

  117. Ma, L., Tan, T., Wang, Y., Zhang, D.: Local intensity variation analysis for iris recognition. Pattern Recognit. 37(6), 1287–1298 (2004)

    Article  Google Scholar 

  118. Masek, L.: Iris recognition (2003)

    Google Scholar 

  119. Matey, J.R., Kennell, L.R.: Iris recognition – beyond one meter. In: Handbook of Remote Biometrics (2009)

    Google Scholar 

  120. Matey, J.R., Naroditsky, O.: Iris on the move: acquisition of images for iris recognition in less constrained environments. Proc. IEEE 94(11), 1936–1947 (2006)

    Article  Google Scholar 

  121. McCloskey, S., Au, A.W., Jelinek, J.: Iris capture from moving subjects using a fluttering shutter. In: Fourth IEEE International Conference on Biometrics: Theory Applications and Systems (BTAS) (2010)

    Google Scholar 

  122. Mehrotra, H., Majhi, B., Gupta, P.: Annular iris recognition using SURF. In: Pattern Recognition and Machine Intelligence: Lecture Notes in Computer Science #5909, pp. 464–469 (2009)

    Google Scholar 

  123. Mehrotra, H., Badrinath, G.S., Majhi, B., Gupta, P.: An efficient dual stage approach for iris feature extraction using interest point pairing. In: IEEE Workshop on Computational Intelligence in Biometrics: Theory, Algorithms, and Applications (CIB), pp. 59–62 (2009)

    Google Scholar 

  124. Mehrotra, H., Srinivas, B.G., Majhi, B., Gupta, P.: Indexing iris biometric database using energy histogram of DCT subbands. Contemp. Comput. 40(4), 194–204 (2009)

    Article  Google Scholar 

  125. Merkow, J., Jou, B., Savvides, M.: An exploration of gender identification using only the periocular region. In: Fourth IEEE International Conference on Biometrics: Theory Applications and Systems (BTAS) (2010)

    Google Scholar 

  126. Miller, P.E., Lyle, J.R., Pundlik, S.J., Woodard, D.L.: Performance evaluation of local appearance based periocular recognition. In: Fourth IEEE International Conference on Biometrics: Theory Applications and Systems (BTAS) (2010)

    Google Scholar 

  127. Mishra, R., Pathak, V.: Human recognition using fusion of iris and ear data. In: International Conference on Methods and Models in Computer Science (ICM2CS), pp. 1–5 (2009)

    Google Scholar 

  128. Miyazawa, K., Ito, K., Aoki, T., Kobayashi, K.: An effective approach for iris recognition using phase-based image matching. IEEE Trans. Pattern Anal. Mach. Intell. 30(10), 1741–1756 (2008)

    Article  Google Scholar 

  129. Mohammadi, S., Jahanshahi, H.: A secure e-tendering system. In: IEEE International Conference on Electro/Information Technology (EIT), pp. 62–67 (2009)

    Google Scholar 

  130. Moi, S.H., Rahim, N., Abdul, B. et al.: iris biometric cryptography for identity document. International Conference of Soft Computing and Pattern Recognition (SOCPAR), pp. 736–741 (2009)

    Google Scholar 

  131. Mondal, A., Roy, K., Bhattacharya, P.: Secure and simplified access to home appliances using iris recognition. In: IEEE Workshop on Computational Intelligence in Biometrics: Theory, Algorithms, and Applications (CIB), pp. 22–29 (2009)

    Google Scholar 

  132. Moravec, P., Gajdos, P., Snasel, V., Saeed, K.: Normalization impact on SVD-based iris recognition. In: International Conference on Biometrics and Kansei Engineering (ICBAKE), pp. 60–64 (2009)

    Google Scholar 

  133. Morizet, N., Gilles, J.: A new adaptive combination approach to score level fusion for face and iris biometrics combining wavelets and statistical moments. In: Advances in Visual Computing: Lecture Notes in Computer Science #5359, pp. 661–671 (2008)

    Google Scholar 

  134. Munemoto, T., Li, Y.H., Savvides, M.: Hallucinating irises – dealing with partial and occluded iris regions. In: IEEE 2nd International Conference on Biometrics: Theory, Applications, and Systems (BTAS) (2008)

    Google Scholar 

  135. Newton, E.M., Phillips, P.J.: Meta-analysis of third-party evaluations of iris recognition. IEEE Trans. Syst. Man Cybern. 39(1), 4–11 (2009)

    Article  Google Scholar 

  136. Ortega-Garcia, J., Fierrez, J., Alonso-Fernandez, F., Galbally, J.: The multi-scenario multi-environment biosecure multimodal database (BMDB). IEEE Trans. Pattern Anal. Mach. Intell. 32(6), 1097–1111 (2010)

    Article  Google Scholar 

  137. Pan, L., Xie, M., Zheng, T., Ren, J.: A robust iris localization model based on phase congruency and least trimmed squares estimation. In: Image Analysis and Processing -ICIAP Lecture Notes in Computer Science #5716, pp. 682–691 (2009)

    Google Scholar 

  138. Patil, C.M., Patilkulkarani, S.: A comparative study of feature extraction approaches for an efficient iris recognition system. In: Information Processing and Management, pp. 411–416 (2010)

    Google Scholar 

  139. Patil, C.M., Patilkulkarani, S.: An approach to enhance security environment based on SIFT feature extraction and matching to iris recognition. In: Information Processing and Management, pp. 527–530 (2010)

    Google Scholar 

  140. Patil, C.M., Patilkulkarani, S.: Iris feature extraction for personal identification using lifting wavelet transform. In: International Conference on Advances in Computing, Control, and Telecommunication Technologies (ACT), pp. 764–766 (2009)

    Google Scholar 

  141. Petrovska-Delacretaz, D., Mayoue, A., Dorizzi, B.: The biosecure benchmarking methodology for biometric performance evaluation. In: Guide to Biometric Reference Systems and Performance Evaluation (2009)

    Google Scholar 

  142. Phillips, P.J., Beveridge, J.R.: An introduction to biometric-completeness: The equivalence of matching and quality. In: IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems (BTAS), pp. 1–5 (2009)

    Google Scholar 

  143. Phillips, P.J., Newton, E.M.: Biometric systems: the rubber meets the road. Proc. IEEE 97(5), 782–783 (2009)

    Article  Google Scholar 

  144. Phillips, P.J., Bowyer, K.W., Flynn, P.J.: Comment on the CASIA version 1.0 iris dataset. IEEE Trans. Pattern Anal. Mach. Intell. 29(10), 1869–1870 (2007)

    Google Scholar 

  145. Phillips, P.J., Bowyer, K.W., Flynn, P.J., Liu, X., Scruggs, W.T.: The iris challenge evaluation 2005. In: 2nd IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS) (2008)

    Google Scholar 

  146. Phillips, P., Scruggs, T., Flynn, P., Bowyer, K., et al.: Overview of the multiple biometric grand challenge. In: International Conference on Biometrics: Lecture Notes in Computer Science, vol. 5558, pp. 705–714 (2009)

    Article  Google Scholar 

  147. Phillips, P.J., Scruggs, W., O’Toole, A., Flynn, P., Bowyer, K.W., Schott, C., Sharpe, M.: FRVT 2006 and ICE 2006 large-scale experimental results. IEEE Trans. Pattern Anal. Mach. Intell. 32(5), 831–846 (2010)

    Article  Google Scholar 

  148. Pillai, J.K., Patel, V.M., Chellappa, R.: Sparsity inspired selection and recognition of iris images. In: IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems (BTAS), pp. 1–6 (2009)

    Google Scholar 

  149. Plaga, R.: Biometric keys: suitable use cases and achievable information content. Int. J. Inf. Secur. 8, 447–454 (2009)

    Article  Google Scholar 

  150. Poh, N., Bourlai, T., Kittler, J., Allano, L., Alonso-Fernandez, F.: Benchmarking quality-dependent and cost-sensitive score-level multimodal biometric fusion algorithms. IEEE Trans. Inf. Forensics Secur. 4(4), 849–866 (2009)

    Article  Google Scholar 

  151. Proenca, H.: Iris recognition: a method to segment visible wavelength iris images acquired on-the-move and at-a-distance. In: Advances in Visual Computing: Lecture Notes in Computer Science #5358, vol. 32(8), pp. 731–742 (2008)

    Google Scholar 

  152. Proenca, H.: On the feasibility of the visible wavelength, at-a-distance and on-the-move iris recognition. In: IEEE Workshop on Computational Intelligence in Biometrics: Theory, Algorithms, and Applications (CIB), pp. 9–15 (2009)

    Google Scholar 

  153. Proenca, H.: Iris recognition: On the segmentation of degraded images acquired in the visible wavelength. IEEE Trans. Pattern Anal. Mach. Intell. 32(8), 1502–1516 (2010)

    Article  Google Scholar 

  154. Proenca, H.: Quality assessment of degraded iris images acquired in the visible wavelength. IEEE Trans. Inf. Forensics Secur. 6(1), 82–95 (2011)

    Article  Google Scholar 

  155. Proenca, H., Filipe, S., Santos, R., Oliveira, J., Alexandre, L.: The UBIRIS.v2: a database of visible wavelength images captured on-the-move and at-a-distance. IEEE Trans. Pattern Anal. Mach. Intell. 32(8), 1529–1535 (2010)

    Google Scholar 

  156. Pundlik, S.J., Woodard, D.L., Birchfield, S.T.: Non-ideal iris segmentation using graph cuts. In: IEEE CVPR Workshop on Biometrics (2008)

    Google Scholar 

  157. Rachubinski, M.: Iris identification using geometrical wavelets. In: Computer Vision and Graphics (2009)

    Google Scholar 

  158. Radhika, K., Sheela, S., Venkatesha, M., Sekhar, G.: Multi-modal authentication using continuous dynamic programming. In: Biometric ID Management and Multimodal Communication: Lecture Notes in Computer Science #5707, pp. 228–235 (2009)

    Google Scholar 

  159. Rakvic, R.N., Ulis, B.J., Broussard, R.P., Ives, R.W., Steiner, N.: Parallelizing iris recognition. IEEE Trans. Inf. Forensics Secur. 4(4), 812–823 (2009)

    Article  Google Scholar 

  160. Rankin, D., Scotney, B., Morrow, P., McDowell, R., Pierscionek, B.: Comparing and improving algorithms for iris recognition. In: 13th International Machine Vision and Image Processing Conference (IMVIP), pp. 99–104 (2009)

    Google Scholar 

  161. Ratha, N.K.: Privacy protection in high security biometrics applications. In: Ethics and Policy of Biometrics: Lecture Notes in Computer Science #6005, pp. 62–69 (2010)

    Google Scholar 

  162. Rathgeb, C., Uhl, A.: Systematic construction of iris-based fuzzy commitment schemes. In: Advances in Biometrics: Lecture Notes in Computer Science #5558, pp. 940–949 (2009)

    Google Scholar 

  163. Rathgeb, C., Uhl, A.: Privacy preserving key generation for iris biometrics. In: Communications and Multimedia Security: Lecture Notes in Computer Science #6109, pp. 191–200 (2010)

    Google Scholar 

  164. Rathgeb, C., Uhl, A.: Two-factor authentication or how to potentially counterfeit experimental results in biometric systems. In: ICIAR 2010: Lecture Notes in Computer Science #6112, pp. 296–305 (2010)

    Google Scholar 

  165. Rathgeb, C., Uhl, A., Wild, P.: Incremental iris recognition: a single-algorithm serial fusion strategy to optimize time complexity. In: Fourth IEEE International Conference on Biometrics: Theory Applications and Systems (BTAS) (2010)

    Google Scholar 

  166. Rattani, A., Tistarelli, M.: Robust multi-modal and multi-unit feature level fusion of face and iris biometrics. In: Advances in Biometrics: Lecture Notes in Computer Science #5558, pp. 960–969 (2009)

    Google Scholar 

  167. Ren, J., Xie, M.: Evaluation of iris images definition based on pupil’s edge kurtosis. In: 2nd International Congress on Image and Signal Processing (CISP), pp. 1–4 (2009)

    Google Scholar 

  168. Ren, J., Xie, M.: Research on clarity-evaluation-method for iris images. In: Second International Conference on Intelligent Computation Technology and Automation (ICICTA), vol. 1, pp. 682–685 (2009)

    Google Scholar 

  169. Ricanek, K.: Dissecting the human identity. Computer 44, 96–97 (2011)

    Article  Google Scholar 

  170. Ross, A., Pasula, R., Hornak, L.: Exploring multispectral iris recognition beyond 900nm. In: IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems (BTAS) (2009)

    Google Scholar 

  171. Ross, A., Rattani, A., Tistarelli, M.: Exploiting the doddington zoo effect in biometric fusion. In: IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems (BTAS) (2009)

    Google Scholar 

  172. Roy, K., Bhattacharya, P.: Improving features subset selection using genetic algorithms for iris recognition. In: Artificial Neural Networks in Pattern Recognition: Lecture Notes in Computer Science #5064, pp. 292–304 (2008)

    Google Scholar 

  173. Roy, K., Bhattacharya, P.: Optimal features subset selection using genetic algorithms for iris recognition. In: Image Analysis and Recognition: Lecture Notes in Computer Science #5112, pp. 894–904 (2008)

    Google Scholar 

  174. Roy, K., Bhattacharya, P.: Iris recognition in nonideal situations. In: Information Security: Lecture Notes in Computer Science #5735, pp. 143–150 (2009)

    Google Scholar 

  175. Roy, K., Bhattacharya, P.: Level set approaches and adaptive asymmetrical SVMs applied for nonideal iris recognition. In: Image Analysis and Recognition: Lecture Notes in Computer Science #5627, pp. 418–428 (2009)

    Google Scholar 

  176. Roy, K., Bhattacharya, P.: Nonideal iris recognition using level set approach and coalitional game theory. In: Computer Vision Systems: Lecture Notes in Computer Science #5815, pp. 394–402 (2009)

    Google Scholar 

  177. Roy, K., Bhattacharya, P.: Unideal iris segmentation using region-based active contour model. In: ICIAR Lecture Notes in Computer Science #6112, pp. 256–265 (2010)

    Google Scholar 

  178. Ruiz-Albacete, V., Tome-Gonzalez, P., Alonso-Fernandez, F.: Direct attacks using fake images in iris verification. In: Biometrics and Identity Management: Lecture Notes in Computer Science #5372, pp. 181–190 (2008)

    Google Scholar 

  179. Ryan, W.J., Woodard, D.L., Duchowski, A.T., Birchfield, S.T.: Adapting starburst for elliptical iris segmentation. In: IEEE 2nd International Conference on Biometrics: Theory, Applications, and Systems (BTAS) (2008)

    Google Scholar 

  180. Scallan, J.A., Weimer, S.: Overview of the Multiple Biometrics Grand Challenge, vol. 5558, pp. 705–714. Springer, Berlin/Heidelberg (2009)

    Google Scholar 

  181. Schmid, N.A., Nicolò, F.: On empirical recognition capacity of biometric systems under global PCA and ICA encoding. IEEE Trans. Inf. Forensics Secur. 3(3), 512–528 (2008)

    Article  Google Scholar 

  182. Schmid, N.A., Nicolo, F.: A method for selecting and ranking quality metrics for optimization of biometric recognition systems. In: Computer Vision and Pattern Recognition Workshops (CVPR Workshops), pp. 126–133 (2009)

    Google Scholar 

  183. Scotti, F., Piuri, V.: Adaptive reflection detection and location in iris biometric images by using computational intelligence techniques. IEEE Trans. Instrum. Meas. 59(7), 1825–1833 (2010)

    Article  Google Scholar 

  184. Shah, S., Ross, A.: Iris segmentation using geodesic active contours. IEEE Trans. Inf. Forensics Secur. 4(4), 824–836 (2009)

    Article  Google Scholar 

  185. Sheela, S., Radhika, K., Venkatesha, M., Vijaya, P.: Iris and signature authentication using continuous dynamic programming. In: 2nd International Congress on Image and Signal Processing (CISP), pp. 1–5 (2009)

    Google Scholar 

  186. Stark, L., Bowyer, K.W., Siena, S.: Human perceptual categorization of iris texture patterns. In: Fourth IEEE International Conference on Biometrics: Theory Applications and Systems (BTAS) (2010)

    Google Scholar 

  187. Sudha, N., Puhan, N.B., Xia, H., Jiang, X.: Iris recognition on edge maps. IET Comput. Vis. 3(1), 1–7 (2009)

    Article  Google Scholar 

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

    Article  Google Scholar 

  189. Tajbakhsh, N., Araabi, B., Soltanian-zadeh, H.: Noisy iris verification: a modified version of local intensity variation method. In: Advances in Biometrics: Lecture Notes in Computer Science #5558, pp. 1150–1159 (2009)

    Google Scholar 

  190. Tajbakhsh, N., Misaghian, K., Bandari, N.: A region-based iris feature extraction method based on 2D-wavelet transform. In: Biometric ID Management and Multimodal Communication: Lecture Notes in Computer Science #5707, pp. 301–307 (2009)

    Google Scholar 

  191. Takano, H., Nakamura, K.: Rotation independent iris recognition by the rotation spreading neural network. In: IEEE 13th International Symposium on Consumer Electronics (ISCE), pp.  651–654 (2009)

    Google Scholar 

  192. Tan, F., Ong, T.S., Tee, C., Teoh, A.B.J.: Image hashing enabled technique for biometric template protection. In: IEEE Region 10 Conference (TENCON), pp. 1–5 (2009)

    Google Scholar 

  193. Tayal, A., Balasubramaniam, R., Kumar, A., Bahattacharjee, A., Saggi, M.: A multimodal biometric authentication system using decision theory, iris and speech recognition. In: 2nd International Workshop on Nonlinear Dynamics and Synchronization (INDS), pp. 1–8 (2009)

    Google Scholar 

  194. Tayal, A., Balasubramaniam, R., Kumar, A., Bhattacharjee, A., Saggi, M.: A multimodal biometric system coupling iris recognition and speaker identification systems through decision theory. In: 3rd International Conference on Anti-counterfeiting, Security, and Identification in Communication (ASID), pp. 135–137 (2009)

    Google Scholar 

  195. Thompson, J.W., Flynn, P.J.: A segmentation perturbation method for improved iris recognition. In: Fourth IEEE International Conference on Biometrics: Theory Applications and Systems (BTAS) (2010)

    Google Scholar 

  196. Vandal, N.A., Savvides, M.: CUDA accelerated iris template matching on graphics processing units. In: Fourth IEEE International Conference on Biometrics: Theory Applications and Systems (BTAS) (2010)

    Google Scholar 

  197. Vatsa, M., Singh, R., Noore, A.: Improving iris recognition performance using segmentation, quality enhancement, match score fusion, and indexing. IEEE Trans. Syst. Man Cybern. 38(4), 1021–1035 (2008)

    Article  Google Scholar 

  198. Vatsa, M., Singh, R., Noore, A., Singh, S.K.: Belief function theory based biometric match score fusion: case studies in multi-instance and multi-unit iris verification. In: Seventh International Conference on Advances in Pattern Recognition (ICAPR), pp. 433–436 (2009)

    Google Scholar 

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

    Article  Google Scholar 

  200. Wang, F., Han, J.: Multimodal biometric authentication based on score level fusion using support vector machine. In: Opto-Electronics Review, vol. 17, pp. 59–64 (2009)

    Article  Google Scholar 

  201. Wang, D., Li, J., Memik, G.: Authentication scheme of DRM system for remote users based on multimodal biometrics, watermarking and smart card. In: WRI Global Congress on Intelligent Systems (GCIS), vol. 2, pp. 530–534 (2009)

    Google Scholar 

  202. Wang, J., Li, Y., Ao, X., Wang, C., Zhou, J.: Multi-modal biometric authentication fusing iris and palmprint based on GMM. In: IEEE 15th Workshop on Statistical Signal Processing (SSP), pp. 349–352 (2009)

    Google Scholar 

  203. Wang, X., Zhao, L., Kong, Q.: Iris recognition system design and development of large animals for tracing source of infection. Int. Joint Conf. Comput. Sci. Optim. 1, 610–613 (2009)

    Google Scholar 

  204. Wang, Z.F., Han, Q., Li, Q., Niu, X.M., Busch, C.: Complex common vector for multimodal biometric recognition. Electronics Lett. 45(10), 495–496 (2009)

    Article  Google Scholar 

  205. Wang, Z., Han, Q., Niu, X., Busch, C.: Feature-level fusion of iris and face for personal identification. In: Advances in Neural Networks – ISNN 2009: Lecture Notes in Computer Science #5553, pp. 356–364 (2009)

    Google Scholar 

  206. Wang, Z., Li, Q., Niu, X., Busch, C.: Multimodal biometric recognition based on complex KFDA. In: Fifth International Conference on Information Assurance and Security (IAS), vol. 2, pp. 177–180 (2009)

    Google Scholar 

  207. Wei, Z., Qiu, X., Sun, Z., Tan, T.: Counterfeit iris detection based on texture analysis. In: 19th International Conference on Pattern Recognition (2008)

    Google Scholar 

  208. Wheeler, F.W., Perera, A.G.A., Abramovich, G., Yu, B., Tu, P.H.: Stand-off iris recognition system. In: IEEE 2nd International Conference on Biometrics: Theory, Applications, and Systems (BTAS) (2008)

    Google Scholar 

  209. Wibowo, E.P., Maulana, W.S.: Real-time iris recognition system using a proposed method. In: International Conference on Signal Processing Systems, pp. 98–102 (2009)

    Google Scholar 

  210. Wu, D.M., Wang, J.N.: An improved iris recognition method based on gray surface matching. In: Fifth International Conference on Information Assurance and Security (IAS), vol. 1, 247–249 (2009)

    Google Scholar 

  211. Xiangde, Z., Qi, W., Hegui, Z., Cuili, Y., Longcheng, G., Xianyan, L.: Noise detection of iris image based on texture analysis. In: Chinese Control and Decision Conference (CCDC), pp. 2366–2370 (2009)

    Google Scholar 

  212. Xu, X., Guo, P.: Iris feature extraction based on the complete 2DPCA. In: Advances in Neural Networks: Lecture Notes in Computer Science #5552, pp. 950–958 (2009)

    Google Scholar 

  213. Xu, J., Cha, M., Heyman, J.L., Venugopalan, S., Abiantun, R., Savvides, M.: Robust local binary pattern feature sets for periocular biometric identification. In: Fourth IEEE International Conference on Biometrics: Theory Applications and Systems (BTAS) (2010)

    Google Scholar 

  214. Yager, N., Dunstone, T.: The biometric menagerie. IEEE Trans. Pattern Anal. Mach. Intell. 32(2), 220–230 (2010)

    Article  Google Scholar 

  215. Zhang, L., Sun, Z., Tan, T., Hu, S.: Robust biometric key extraction based on iris cryptosystem. In: Advances in Biometrics: Lecture Notes in Computer Science #5558 (2009)

    Google Scholar 

  216. Zhao, X., Xie, M.: A practical design of iris recognition system based on DSP. In: International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC), vol. 1, pp. 66–70 (2009)

    Google Scholar 

  217. Zhiping, Z., Maomao, H., Ziwen, S.: An iris recognition method based on 2DWPCA and neural network. In: Chinese Control and Decision Conference (CCDC), pp. 2357–2360 (2009)

    Google Scholar 

  218. Zhou, Z., Du, Y., Belcher, C.: Transforming traditional iris recognition systems to work in nonideal situations. IEEE Trans. Ind. Electron. 56(8), 3203–3213 (2009)

    Article  Google Scholar 

  219. Zhou, Z., Du, Y., Belcher, C.: Transforming traditional iris recognition systems to work on non-ideal situations. In: IEEE Workshop on Computational Intelligence in Biometrics: Theory, Algorithms, and Applications (CIB), pp. 1–8 (2009)

    Google Scholar 

  220. Zuo, J., Schmid, N.A.: Global and local quality measures for NIR iris video. In: Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 120–125 (2009)

    Google Scholar 

  221. Zuo, J., Schmid, N.A.: On a methodology for robust segmentation of nonideal iris images. IEEE Trans. Syst. Man Cybern. 40(3), 703–718 (2010)

    Article  Google Scholar 

  222. Zuo, J., Nicolo, F., Schmid, N.A.: Cross spectral iris matching based on predictive image mapping. In: Fourth IEEE International Conference on Biometrics: Theory Applications and Systems (BTAS) (2010)

    Google Scholar 

Download references

Acknowledgements

The authors were supported by the Federal Bureau of Investigation, the Central Intelligence Agency, the Intelligence Advanced Research Projects Activity, the Biometrics Task Force, the Technical Support Working Group under US Army contract W91CRB-08-C-0093, and the Intelligence Community Postdoctoral Fellowship Program.

The opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of our sponsors. The identification of any commercial product or trade name does not imply endorsement or recommendation by the authors, the University of Notre Dame, or the National Institute of Standards and Technology.

Author information

Authors and Affiliations

  1. University of Notre Dame, IN, USA

    Kevin W. Bowyer, Karen P. Hollingsworth & Patrick J. Flynn

Authors
  1. Kevin W. Bowyer
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Karen P. Hollingsworth
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Patrick J. Flynn
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kevin W. Bowyer .

Editor information

Editors and Affiliations

  1. MITRE Corporation, Colshire Drive 7515, McLean, 22102-7539, Virginia, USA

    Mark J. Burge

  2. , Department of Computer Science and Engin, University of Notre Dame, Fitzpatrick Hall 384, Notre Dame, 46556-5637, Indiana, USA

    Kevin W. Bowyer

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag London

About this chapter

Cite this chapter

Bowyer, K.W., Hollingsworth, K.P., Flynn, P.J. (2013). A Survey of Iris Biometrics Research: 2008–2010. In: Burge, M., Bowyer, K. (eds) Handbook of Iris Recognition. Advances in Computer Vision and Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-4471-4402-1_2

Download citation

  • DOI: https://doi.org/10.1007/978-1-4471-4402-1_2

  • Published:

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-4401-4

  • Online ISBN: 978-1-4471-4402-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation