Iris recognition

Iris recognition biometric systems apply mathematical pattern-recognition techniques to images of the irises of an individual's eyes.

Iris recognition is an automated method of biometric identification that uses mathematical pattern-recognition techniques on video images of one or both of the irises of an individual's eyes, whose complex patterns are unique, stable, and can be seen from some distance. The discriminating powers of all biometric technologies depend on the amount of entropy[1] they are able to encode and use in matching. Iris recognition is exceptional in this regard, enabling the avoidance of "collisions" (False Matches) even in cross-comparisons across massive populations.[2] Its major limitation is that image acquisition from distances greater than a meter or two, or without cooperation, can be very difficult. However, the technology is in development and iris recognition can be accomplished from even up to 10 meters away or in a live camera feed.[3]

Retinal scanning is a different, ocular-based biometric technology that uses the unique patterns on a person's retina blood vessels and is often confused with iris recognition. Iris recognition uses video camera technology with subtle near infrared illumination to acquire images of the detail-rich, intricate structures of the iris which are visible externally. Digital templates encoded from these patterns by mathematical and statistical algorithms allow the identification of an individual or someone pretending to be that individual.[4] Databases of enrolled templates are searched by matcher engines at speeds measured in the millions of templates per second per (single-core) CPU, and with remarkably low false match rates.

At least 1.5 billion people around the world (including 1.29 billion citizens of India, in the UIDAI / Aadhaar programme as updated on 30 November) have been enrolled in iris recognition systems for national ID, e-government services, benefits distribution, security, and convenience purposes such as passport-free automated border-crossings.[5][6][7][8][9][10][11][12] A key advantage of iris recognition, besides its speed of matching and its extreme resistance to false matches, is the stability[13] of the iris as an internal and protected, yet externally visible organ of the eye.

In 2023, Pakistan's National Database & Registration Authority (NADRA) has launched IRIS for citizen registration/ Civic Management during registration at its offices for the National ID Card. After its initial stage, the eye-recognition verification access will be available for LEAs, banking sectors, etc.

  1. ^ "Advances in Artificial Intelligence and Machine Learning, vol. 4, issue 2, pp 2152-2163" (PDF). cam.ac.uk.
  2. ^ "Understanding Biometric Entropy and Iris Capacity: Avoiding Identity Collisions on National Scales" (PDF). cam.ac.uk. Retrieved 12 August 2023.
  3. ^ Choi, | Tyler (13 June 2022). "Iris recognition reaches the mainstream for identification, authentication | Biometric Update". www.biometricupdate.com. Retrieved 28 June 2023.
  4. ^ Zetter, Kim (25 July 2012). "Reverse-Engineered Irises Look So Real, They Fool Eye-Scanners". Wired Magazine. Retrieved 25 July 2012.
  5. ^ "Apache Tomcat". Archived from the original on 28 June 2013. Retrieved 27 August 2013.
  6. ^ "UNHCR's new biometrics system helps verify 110,000 Myanmar refugees in Thailand | UNHCR UK".
  7. ^ "Blockchain could change the future of humanitarian aid". 3 January 2019.
  8. ^ "WFP Introduces Iris Scan Technology to Provide Food Assistance to Syrian Refugees in Zaatari | World Food Programme". 6 October 2016.
  9. ^ "'These changes show that WFP loves us.'". 20 March 2018.
  10. ^ "A Decade of Aadhaar: Lessons in implementing a foundational ID system | ORF".
  11. ^ "Biometrics on a mass scale".
  12. ^ Daugman, John (7 May 2014). "600 million citizens of India are now enrolled with biometric ID". SPIE Newsroom. SPIE-Intl Soc Optical Eng. doi:10.1117/2.1201405.005449.
  13. ^ P. Grother, J. Matey, E. Tabassi, G. Quinn, and M. Chumakov, IREX VI: temporal stability of iris recognition accuracy, NIST Interagency Report 7948, pp. 1–3, 2013

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