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Fusion of Face and Iris Biometrics

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Handbook of Iris Recognition

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

Abstract

This chapter presents a system which simultaneously acquires face and iris samples using a single sensor, with the goal of improving recognition accuracy while minimizing sensor cost and acquisition time. The resulting system improves recognition rates beyond the observed recognition rates for either isolated biometrics.

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References

  1. Bowyer, K.W., Chang, K.I., Yan, P., Flynn, P.J., Hansley, E., Sarkar, S.: Multi-modal biometrics: an overview. In: Presented at the Second Workshop on Multi-Modal User Authentication (MMUA 2006), Toulouse (2006)

    Google Scholar 

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

    Article  Google Scholar 

  3. Bradski, G., Kaehler, A.: Learning OpenCV. O’Reilly Media, Sebastopol (2008)

    Google Scholar 

  4. Chen, C.H., Te Chu, C.: Fusion of face and iris features for multimodal biometrics. In: Zhang, D., Jain, A. (eds.) Advances in Biometrics. Lecture Notes in Computer Science, vol. 3832, pp. 571–580. Springer, Berlin/Heidelberg (2005)

    Google Scholar 

  5. Colorado State University: Evaluation of Face Recognition Algorithms. http://www.cs.colostate.edu/evalfacerec/algorithms5.html (2010)

  6. Daugman, J.: How iris recognition works. In: 2002 International Conference on Image Processing, Rochester, vol. 1, pp. 33–36 (2002)

    Google Scholar 

  7. Ko, T.: Multimodal biometric identification for large user population using fingerprint, face and iris recognition. In: 34th Applied Imagery and Pattern Recognition Workshop, Washington, DC, pp. 218–223 (2005)

    Google Scholar 

  8. LG Iris: LG Iris Products and Solutions. http://www.lgiris.com/ps/products/irisaccess4000.htm (2010)

  9. Li, S.Z., Chu, R., Ao, M., Zhang, L., He, R.: Highly accurate and fast face recognition using near infrared images. In: International Conference on Biometrics (ICB 2006), Hong Kong, pp. 151–158 (2006)

    Google Scholar 

  10. Matey, J., Naroditsky, O., Hanna, K., Kolczynski, R., LoIacono, D., Mangru, S., Tinker, M., Zappia, T., Zhao, W.: Iris on the move: acquisition of images for iris recognition in less constrained environments. Proc. IEEE 94, 1936–1947 (2006)

    Article  Google Scholar 

  11. Morizet, N., Gilles, J.: A new adaptive combination approach to score level fusion for face and iris biometrics combining wavelets and statistical moments. In: Bebis, G., Boyle, R., Parvin, B., Koracin, D., Remagnino, P., Porikli, F., Peters, J., Klosowski, J., Arns, L., Chun, Y., Rhyne, T.M., Monroe, L. (eds.) Advances in Visual Computing. Lecture Notes in Computer Science, vol. 5359, pp. 661–671. Springer, Berlin/Heidelberg (2008)

    Google Scholar 

  12. National Institute of Standards and Technology (NIST): Portal Challenge Problem – Multiple Biometric Grand Challenge, Preliminary Results of Version 2. http://biometrics.nist.gov/cs_links/face/mbgc/2009/PORTAL_V2_FINAL.pdf (2009)

  13. Phillips, P.J., Flynn, P.J., Beveridge, J.R., Scruggs, W.T., O’Toole, A.J., David, B., Bowyer, K.W., Draper, B.A., Givens, G.H., Lui, Y.M., Sahibzada, H., Scallan Iii, J.A., Weimer, S.: Overview of the multiple biometrics grand challenge. In: Proceedings of the Third International Conference on Advances in Biometrics, ICB ’09, pp. 705–714. Springer, Berlin/Heidelberg (2009)

    Google Scholar 

  14. Rattani, A., Tistarelli, M.: Robust multi-modal and multi-unit feature level fusion of face and iris biometrics. In: Tistarelli, M., Nixon, M. (eds.) Advances in Biometrics. Lecture Notes in Computer Science, vol. 5558, pp. 960–969. Springer, Berlin/Heidelberg (2009)

    Google Scholar 

  15. Ross, A.: An introduction to multibiometrics. In: 15th European Signal Processing Conference (EUSIPCO), Poznan, pp. 20–24 (2007)

    Google Scholar 

  16. Ross, A., Jain, A.K.: Multimodal biometrics: an overview. In: 12th European Signal Processing Conference (EUSIPCO), Vienna, pp. 1221–1224 (2004)

    Google Scholar 

  17. Ross, A.A., Nandakumar, K., Jain, A.K.: Handbook of Multibiometrics. Springer Science and Business Media. Springer, New York (2006)

    Google Scholar 

  18. Son, B., Lee, Y.: Biometric authentication system using reduced joint feature vector of iris and face. In: Kanade, T., Jain, A., Ratha, N. (eds.) 6th International Conference on Audio- and Video-Based Biometric Person Authentication (AVBPA’03). Lecture Notes in Computer Science, vol. 3546, pp. 513–522. Springer, Berlin/Heidelberg (2005)

    Chapter  Google Scholar 

  19. Turk, M., Pentland, A.: Face recognition using eigenfaces. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR ’91), Lahaina, pp. 586–591 (1991)

    Google Scholar 

  20. Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2001), Kauai, vol. 1, pp. 511–518 (2001)

    Google Scholar 

  21. Volner, R., Bores, P.: Multi-biometric techniques, standards activities and experimenting. In: 2006 International Baltic Electronics Conference, Tallinn, pp. 1–4 (2006)

    Google Scholar 

  22. Wang, Y., Tan, T., Jain, A.K.: Combining face and iris biometrics for identity verification. In: 4th International Conference on Audio- and Video-Based Biometric Person Authentication (AVBPA’03), pp. 805–813. Springer, Berlin/Heidelberg (2003)

    Google Scholar 

  23. Yang, J., Liao, S., Li, S.: Automatic partial face alignment in nir video sequences. In: Tistarelli, M., Nixon, M. (eds.) Advances in Biometrics. Lecture Notes in Computer Science, vol. 5558, pp. 249–258. Springer, Berlin/Heidelberg (2009)

    Google Scholar 

  24. Zhang, Z., Wang, R., Pan, K., Li, S., Zhang, P.: Fusion of near infrared face and iris biometrics. In: Lee, S.W., Li, S. (eds.) Advances in Biometrics. Lecture Notes in Computer Science, vol. 4642, pp. 172–180. Springer, Berlin/Heidelberg (2007)

    Google Scholar 

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Acknowledgements

Datasets used in this work were acquired under funding from the National Science Foundation under grant CNS01-30839, by the Central Intelligence Agency and by the Technical Support Working Group under US Army Contract W91CRB-08-C-0093. The authors were supported by a grant from the Intelligence Advanced Research Projects Activity.

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Authors and Affiliations

  1. University of Notre Dame, Notre Dame, IN, USA

    Ryan Connaughton, Kevin W. Bowyer & Patrick J. Flynn

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  1. Ryan Connaughton
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  2. Kevin W. Bowyer
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  3. Patrick J. Flynn
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Correspondence to Ryan Connaughton .

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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

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Connaughton, R., Bowyer, K.W., Flynn, P.J. (2013). Fusion of Face and Iris Biometrics. 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_12

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  • DOI: https://doi.org/10.1007/978-1-4471-4402-1_12

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  • Print ISBN: 978-1-4471-4401-4

  • Online ISBN: 978-1-4471-4402-1

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