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Iris

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Encyclopedia of Cryptography and Security

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Definition

Iris is the colored organ inside the eye. In the human eye, as illustrated in Fig. 1, the iris is a thin diaphragm that lies behind the cornea and anterior chamber. The muscles of the iris expand and contract the aperture of the iris (also known as pupil) to adjust the amount of light which passes through the lens [14]. In the information technology field, automated pattern recognition of the human iris can be used to identify each person for security purposes and access control (Fig. 1).

Iris. Fig. 1
figure 1_742 figure 1_742

An anatomical view of the human eye

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Recommended Reading

  1. Almeida P (2009) A knowledge-based approach to the iris segmentation problem. Image Vis Comput 28(2):238–245

    Google Scholar 

  2. Bowyer KW, Hollingsworth KP, Flynn PJ (2007) Image understanding for iris biometrics: a survey. Comp Vis Im Understanding 110(2):281–307

    Google Scholar 

  3. Chen Y, Wang J, Adjouadi M (2008) A robust segmentation approach to iris recognition based on video. Proc IEEE-AIPR pp 1–8, ISBN:978-1-4244-3125-0

    Google Scholar 

  4. Chen Y, Adjouadi M, Han C, Wang J, Barreto A, Rishe N, Andrian J (2010) A highly accurate and computationally efficient approach for unconstrained iris segmentation. Image Vis Comput 28(2):261–269

    Google Scholar 

  5. Daugman JG (2001) Statistical richness of visual phase information: update on recognizing persons by their iris patterns. Int J Comput Vis 45(1):25–38

    MATH  Google Scholar 

  6. Daugman JG (2004) How iris recognition works. IEEE T Circ Syst Vid Technol 14(1):21–30

    Google Scholar 

  7. Donida Labati R, Scotti F (2009) Noisy iris segmentation with boundary regularization and reflections removal. Image Vis Comput 28(2):270–277

    Google Scholar 

  8. Huang X, Ren L, Yang R (2009) Image deblurring for less intrusive iris capture, Proceedings of IEEE conference on computer vision and pattern recognition CVPR 2009, 20–25 June 2009, Miami, FL, pp 1558–1565

    Google Scholar 

  9. Jeonga D, Hwanga J, Kangb B, Parka K, Wonc C, Parkd D, Kim J (2009) A new iris segmentation method for non-ideal iris images. Image Vis Comput 28(2):254–260

    Google Scholar 

  10. Kanski JJ (2007) Clinical ophthalmology : a systematic approach. Butterworth-Heinemann/Elsevier, Edinburgh, New York

    Google Scholar 

  11. Lee Y, Phillips PJ, Micheals RJ (2009) An automated video-based system for iris recognition. Proceedings of the third international conference on advances in biometrics, 2–5 June, Alghero, Italy, Oct. 15–17, 2008, pp 1160–1169

    Google Scholar 

  12. Li P, Liu X, Xiao L, Song Q (2009) Robust and accurate iris segmentation in very noisy iris images. Image Vis Comput 28(2): 238–245

    Google Scholar 

  13. Matey JR, Naroditsky O, Hanna K, Kolczynski R, LoIacono D, Mangru S, Tinker M, Zappia T, Zhao WY (2006) Iris on the move: acquisition of images for iris recognition in less constrained environments. Proc IEEE 94(11):1936–1946

    Google Scholar 

  14. Oyster CW (1999) The human eye: structure and function. Sinauer Associates, Sunderland, USA

    Google Scholar 

  15. Proença H (2009) On the feasibility of the visible wavelength, At-A-Distance and On-The-Move iris recognition. IEEE symposium series on computational intelligence in biometrics: theory, algorithms, and applications, Nashville, Tennessee, USA, March 30–April 2, vol 1, p 9–15, ISBN:978-1-4244-2773-4. (invited paper)

    Google Scholar 

  16. Proença H, Filipe S, Santos R, Oliveira J, Alexandre LA (2009) The UBIRIS.v2: a database of visible wavelength iris images captured On-The-Move and At-A-Distance. IEEE T Pattern Anal Mach Intelligence, doi:10.1109/TPAMI.2009.66

    Google Scholar 

  17. Sankowski W, Grabowskia K, Napieralskaa M, Zuberta M, Napieralski A (2009) Reliable algorithm for iris segmentation in eye image. Image Vis Comput 28(2):231–237

    Google Scholar 

  18. Snell RS, Lemp MA (1998) Clinical anatomy of the eye. Blackwell Science, Malden, MA, USA

    Google Scholar 

  19. Tan T, Hea Z, Sun Z (2009) Efficient and robust segmentation of noisy iris images for non-cooperative iris recognition. Image Vis Comput 28(2):223–230

    Google Scholar 

  20. Wheeler FW, Perera AGA, Abramovich G, Yu B, Tu PH (2008) Stand-off Iris recognition system, Proceedings of 2nd IEEE international conference on biometrics: theory, applications and systems. BTAS 2008, Sept. 29-Oct.1, 2008, Washington DC, pp 1–7

    Google Scholar 

  21. Wildes R (1997) Iris recognition: an emerging biometric technology. Proc IEEE 85:1348–1363

    Google Scholar 

  22. Zhou Z, Du Y, Belcher C (2009) Transforming traditional iris recognition systems to work on non-ideal situations. IEEE T Industry Electronics 56(8):3203–3213

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Florida International University, Miami, Florida

    Yu Chen

Authors
  1. Yu Chen
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Editors and Affiliations

  1. Department of Mathematics and Computing Science, Eindhoven University of Technology, 5600 MB, Eindhoven, The Netherlands

    Henk C. A. van Tilborg

  2. Center for Secure Information Systems, George Mason University, Fairfax, VA, 22030-4422, USA

    Sushil Jajodia

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Chen, Y. (2011). Iris. In: van Tilborg, H.C.A., Jajodia, S. (eds) Encyclopedia of Cryptography and Security. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-5906-5_742

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