World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
33530
World Ranking
7340
National Ranking
439

Research.com Recognitions

  • 2015 - Fellow of the Royal Academy of Engineering (UK)
  • 2015 - Fellow, National Academy of Inventors
  • 2012 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to computer vision, pattern recognition and biometrics

Overview

John Daugman is affiliated with the University of Cambridge in the United Kingdom. Their research primarily contributes to the field of Computer Science, with a focus on subfields such as Signal Processing, Genetics, Geometry and Topology, Information Systems, and Safety Research.

The main topics covered in Daugman's work include:

  • Biometric Identification and Security
  • Forensic and Genetic Research
  • Morphological variations and asymmetry
  • User Authentication and Security Systems
  • Forensic Fingerprint Detection Methods
  • Authorship Attribution and Profiling
  • Face recognition and analysis

They have published research papers in several academic venues, frequently contributing to:

  • IEEE Transactions on Biometrics Behavior and Identity Science
  • CL Technical Reports
  • arXiv (Cornell University)
  • Advances in Artificial Intelligence and Machine Learning

Some recent papers authored by John Daugman include:

  • Biometric decision landscapes, 2021, CL Technical Reports
  • Results from 200 billion iris cross-comparisons, 2021, CL Technical Reports
  • Broken Symmetries, Random Morphogenesis, and Biometric Distance, 2020, IEEE Transactions on Biometrics Behavior and Identity Science
  • Understanding Biometric Entropy and Iris Capacity: Avoiding Identity Collisions on National Scales, 2024, Advances in Artificial Intelligence and Machine Learning
  • Understanding Biometric Entropy and Iris Capacity: Avoiding Identity Collisions on National Scales, 2023, arXiv (Cornell University)

Frequent coauthors in their publications include:

  • Cathryn Downing
  • Akande Noah Oluwatobi
  • Oluwakemi Christiana Abikoye

John Daugman has received several professional recognitions, including being named Fellow of the National Academy of Inventors in 2015, Fellow of the Royal Academy of Engineering (UK) in 2015, and Fellow of the International Association for Pattern Recognition (IAPR) in 2012, the latter acknowledging contributions to computer vision, pattern recognition, and biometrics.

Best Publications

  • High confidence visual recognition of persons by a test of statistical independence

    J.G. Daugman

  • How iris recognition works

    J. Daugman

  • Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters.

    John G. Daugman

  • Complete discrete 2-D Gabor transforms by neural networks for image analysis and compression

    J.G. Daugman

  • Two-dimensional spectral analysis of cortical receptive field profiles.

    John G. Daugman

  • New Methods in Iris Recognition

    J. Daugman

  • The importance of being random: statistical principles of iris recognition

    John Daugman

  • Biometric personal identification system based on iris analysis.

    John G. Daugman

  • Combining Crypto with Biometrics Effectively

    F. Hao;R. Anderson;J. Daugman

  • Probing the Uniqueness and Randomness of IrisCodes: Results From 200 Billion Iris Pair Comparisons

    J. Daugman

  • How iris recognition works

    J. Daugman

  • Statistical Richness of Visual Phase Information: Update on Recognizing Persons by Iris Patterns

    John Daugman

  • DEMODULATION BY COMPLEX-VALUED WAVELETS FOR STOCHASTIC PATTERN RECOGNITION

    John Daugman

  • Epigenetic randomness, complexity and singularity of human iris patterns.

    John Daugman;Cathryn Downing

  • Biometric decision landscapes

    John Daugman

  • Face and gesture recognition: overview

    J. Daugman

  • Spatial visual channels in the fourier plane

    John G. Daugman

  • Entropy reduction and decorrelation in visual coding by oriented neural receptive fields

    J.G. Daugman

  • Combining cryptography with biometrics effectively

    Feng Hao;Ross Anderson;John Daugman

  • Effect of Severe Image Compression on Iris Recognition Performance

    J. Daugman;C. Downing

Frequent Co-Authors

Ross Anderson
Ross Anderson University of Cambridge
Daniel M. Kammen
Daniel M. Kammen University of California, Berkeley
Martin D. Levine
Martin D. Levine McGill University

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