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Iris Image Data Interchange Formats, Standardization

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Encyclopedia of Biometrics

Synonyms

Iris interchange format standards; Iris data interchange standards

Definition

Iris recognition is a biometric technology that uses the unique, stable, and repeatable texture patterns observed within the iris of the human eye, the colored annular ring that surrounds the pupil. Iris recognition systems typically consist of specialized cameras and software that processes images of the eye to extract and encode iris features in a template, and match the presented iris templates to those in a database to identify the individual. Applications include controlled access to buildings, border security, trusted traveler programs, and authentication of emergency aid, entitlement, and citizen benefit recipients. Iris image interchange standards have been developed to facilitate the exchange of iris image data among diverse cameras, processing algorithms, and biometric databases. Existing standards include ANSI INCITS 379 Iris Image Interchange Format and ISO/IEC 19794-6 Information...

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References

  1. Flom, L., Safir, A.: Iris recognition system, US Patent No. 4,641,349, United States Patent and Trademark Office, Washington DC, (1984)

    Google Scholar 

  2. Kim, D., Ryoo, J.: Iris identification system and method of identifying a person through iris recognition, US Patent No. 6,247,813, United States Patent and Trademark Office, (2001)

    Google Scholar 

  3. Monro, D., Rakshit, S., Zhang.: DCT-Based Iris Recognition. IEEE Trans. Pattern Anal. Mach. Intell. 29(4), 586–595 (2007)

    Article  Google Scholar 

  4. Wildes, R., Asmuth, J., Hanna, K., Hsu, S., Kolczynski, R., Matey, J., McBride, S.: Automated, non-invasive iris recognition system and method, US Patent No. 5,572,596, United States Patent and Trademark Office, (1996)

    Google Scholar 

  5. Daugman, J.: High confidence visual recognition of persons by a test of statistical independence. IEEE Trans. Pattern Anal. Mach. Intell. 15(11), 1148–1160, (1993)

    Article  Google Scholar 

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

    Article  Google Scholar 

  7. Masek, L.: Recognition of human iris patterns for biometric identification, Bachelor of Engineering thesis, School of Computer Science and Software Engineering, The University of Western Australia, (2003)

    Google Scholar 

  8. Tisse, C., Martin, L., Torres, L., Robert, M.: Person identification technique using iris recognition, In: Proceedings of the 15th International Conference on Vision Interface, Calgary, Italy, pp. 294–299 (May 29, 2006)

    Google Scholar 

  9. ANSI INCITS 379-2004 Iris image interchange format. American National Standards Institute, (2004)

    Google Scholar 

  10. ISO/IEC 19794-6: 2005 Information technology – Biometric data interchange formats – Part 6: Iris image data, International Standards Organization, (2005)

    Google Scholar 

  11. ISO/IEC 19785-1:2006 Information technology – Common biometric exchange formats framework – Part 1: Data element specification, International Standards Organization, (2006)

    Google Scholar 

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Cambier, J.L. (2009). Iris Image Data Interchange Formats, Standardization. In: Li, S.Z., Jain, A. (eds) Encyclopedia of Biometrics. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-73003-5_238

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