The importance of being random: statistical principles of iris recognition

By John G. Daugman. Pattern Recognition, 2003

1,060 citations recorded by the source corpus.

Subfields: Molecular Biology, Signal Processing

View Paper: https://www.semanticscholar.org/paper/15a31da6f46568aec41ed394cd77a72cb8c7d4bb

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Citations in the corpus

An Online System of Multispectral Palmprint Verification (2010, background): “7 shows some feature maps extracted from Fig.”
Probing the Uniqueness and Randomness of IrisCodes: Results From 200 Billion Iris Pair Comparisons (2006, background): “All foreign nationals who possess a visa to enter the UAE must look at an iris camera, installed at immigration desks.”
DCT-Based Iris Recognition (2007, methodology): “Pioneering work on iris recognition was done by Daugman using Gabor wavelets [10], [11], [12].”
A survey on biometric cryptosystems and cancelable biometrics (2011, background): “, not only the entropy of the entire biometric template (which is commonly estimated in “degrees-of-freedom” [196]) but the distribution of Database”
Image understanding for iris biometrics: A survey (2008, background): “Daugman’s 2003 paper [32] presents similar results as [36], but with a larger dataset of 9.”
Biometric Authentication: A Review (2009, neutral): “In template matching, some statistical calculation is done between a stored iris template and a produced [3, 15, 23, 24].”
Combining Crypto with Biometrics Effectively (2006, methodology): “The design was driven by the error characteristics of iris codes, which are 256-byte strings of phase information derived from an infrared image of an iris by demodulating it with complex-valued 2D Gabor wavelets [3].”
In the Eye of the Beholder: A Survey of Models for Eyes and Gaze (2010, methodology): “Simple ellipse models consist of voting-based methods [79], [84], [111], [118], [142], [165] and model fitting methods [24], [47], [89].”
Multibiometric Cryptosystems Based on Feature-Level Fusion (2012, methodology): “6We use a procedure similar to the one used in [46] to estimate the entropy.”
Automated human identification using ear imaging (2012, background): “Contents lists available at SciVerse ScienceDirect Pattern Recognition 0031-32 doi:10.1 n Corr Polytech fax:þ85 E-m Pleas doi:1 journal homepage: www.elsevier.com/locate/pr Automated human identification using ear imaging Ajay Kumar n, Chenye Wu Department of Computing, The Hong Kong Polytechnic Uni”
Biometrics: a tool for information security (2006, methodology): “The complex iris texture carries very distinctive information useful for personal recognition [11], [71], [72].”
Random Multispace Quantization as an Analytic Mechanism for BioHashing of Biometric and Random Identity Inputs (2006, result): “RMQ authentication is essentially the failure of a test of statistical independence, similar to the Daugman IrisCode [29] prescription.”
50 years of biometric research: Accomplishments, challenges, and opportunities (2016, neutral): “Level 1 features capture macroscopic details Please cite this article as: A.K. Jain et al., 50 years of biometric research: Accomplishments, challenges, and opportunities, Pattern Recognition Letters (2016), http://dx.doi.org/10.1016/j.patrec.2015.12.013”