John Daugman

John Daugman
Residence Cambridge, England
Citizenship British and American
Fields
Institutions
Alma mater Harvard University (AB, PhD)
Known for
  • Theory of vision and pattern recognition; 2D wavelet encodings;

iris recognition algorithm[1]

Notable awards
Website
www.cl.cam.ac.uk/~jgd1000/

John Gustav Daugman OBE FREng FNAI FIMA FBCS FIAPR is a British-American professor of computer vision and pattern recognition at the University of Cambridge. His major research contributions have been in computational neuroscience (wavelet models of mammalian vision), pattern recognition, and in computer vision with the original development of wavelet methods for image encoding and analysis. He invented the IrisCode, a 2D Gabor wavelet-based iris recognition algorithm that is the basis of all publicly deployed automatic iris recognition systems and which has registered more than a billion persons worldwide in government ID programs.[2][3][4][5][6][7]

Education and early life

The son of émigrés Josef Petros Daugmanis from Latvia and Runa Inge Olsson from Sweden, John Daugman was educated in America, receiving an A.B. degree and a Ph.D. degree (1983) from Harvard University.

Career and research

Following his PhD, Daugman held a post-doctoral fellowship, then taught at Harvard for five years. After short appointments in Germany and Japan, he joined the University of Cambridge in England to research and to teach computer vision, neural computing, information theory, and pattern recognition. He held the Johann Bernoulli Chair of Mathematics and Informatics at the University of Groningen in the Netherlands, and the Toshiba Endowed Chair at the Tokyo Institute of Technology in Japan [8] before becoming Professor at Cambridge.

Iris recognition algorithm

Daugman filed for a patent for his iris recognition algorithm[1] in 1991 while working at the University of Cambridge.[9] The algorithm was first commercialized in the late 1990s. His algorithm automatically recognizes persons in real-time by encoding the random patterns visible in the iris of the eye from some distance, and applying a powerful test of statistical independence. As of 2015, it was used in many identification applications such as the Unique IDentification Authority of India (UIDAI) for registering all 1.2 billion citizens of India for government services and entitlements, border crossing controls in United Arab Emirates and passport-free immigration in the UK, the Netherlands, United States, Canada, and other countries.[10]

Daugman's algorithm uses a 2D Gabor wavelet transform to extract the phase structure of the iris. This is encoded into a very compact bit stream, the IrisCode, that is stored in a database for identification at search speeds of millions of iris patterns per second per single CPU core.[11]

Awards and honours

Daugman has received several awards, including:[12]

References

  1. 1 2 Daugman, J. (2004). "How Iris Recognition Works". IEEE Transactions on Circuits and Systems for Video Technology. 14: 21. doi:10.1109/TCSVT.2003.818350.
  2. "Biometric personal identification system based on iris analysis". Retrieved 2010-12-06.
  3. John Daugman's publications indexed by the Scopus bibliographic database, a service provided by Elsevier. (subscription required)
  4. Daugman, J.G. (1993). "High confidence visual recognition of persons by a test of statistical independence". IEEE Transactions on Pattern Analysis and Machine Intelligence. 15 (11): 1148. doi:10.1109/34.244676.
  5. Daugman, John G. (1985). "Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters". Journal of the Optical Society of America A. 2 (7): 1160. doi:10.1364/JOSAA.2.001160.
  6. "John Daugman's webpage". University of Cambridge. Archived from the original on 2015-04-29.
  7. "Short biographical sketch, John Daugman". University of Cambridge. Archived from the original on 2014-03-24.
  8. "Plenary Speakers". Retrieved 2011-02-16.
  9. "Research Excellence Framework". Research Excellence Framework. Iris Recognition. Retrieved 25 April 2015.
  10. Daugman, J. (2015) "Information Theory and the IrisCode". doi:10.1109/TIFS.2015.2500196
  11. John Daugman. "How Iris Recognition Works". CiteSeerX 10.1.1.6.2684Freely accessible.
  12. "American Scientist Online". Retrieved 2011-02-16.
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