Large data analysis: automatic visual personal identification in a demography of 1.2 billion persons

John Daugman

doi:10.1117/12.2053021

22 May 2014 Large data analysis: automatic visual personal identification in a demography of 1.2 billion persons

John Daugman

Proceedings Volume 9118, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XII; 911802 (2014) https://doi.org/10.1117/12.2053021
Event: SPIE Sensing Technology + Applications, 2014, Baltimore, MD, United States

Abstract

The largest biometric deployment in history is now underway in India, where the Government is enrolling the iris patterns (among other data) of all 1.2 billion citizens. The purpose of the Unique Identification Authority of India (UIDAI) is to ensure fair access to welfare benefits and entitlements, to reduce fraud, and enhance social inclusion. Only a minority of Indian citizens have bank accounts; only 4 percent possess passports; and less than half of all aid money reaches its intended recipients. A person who lacks any means of establishing their identity is excluded from entitlements and does not officially exist; thus the slogan of UIDAI is: To give the poor an identity." This ambitious program enrolls a million people every day, across 36,000 stations run by 83 agencies, with a 3-year completion target for the entire national population. The halfway point was recently passed with more than 600 million persons now enrolled. In order to detect and prevent duplicate identities, every iris pattern that is enrolled is first compared against all others enrolled so far; thus the daily workflow now requires 600 trillion (or 600 million-million) iris cross-comparisons. Avoiding identity collisions (False Matches) requires high biometric entropy, and achieving the tremendous match speed requires phase bit coding. Both of these requirements are being delivered operationally by wavelet methods developed by the author for encoding and comparing iris patterns, which will be the focus of this Large Data Award" presentation.

Citation Download Citation

John Daugman "Large data analysis: automatic visual personal identification in a demography of 1.2 billion persons", Proc. SPIE 9118, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XII, 911802 (22 May 2014); https://doi.org/10.1117/12.2053021

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available