Introduction to the Handbook of Iris Recognition

Iris recognition is both a technology already in successful use in ambitious nation-scale applications and also a vibrant, active research area with many difficult and exciting problems yet to be solved. This chapter gives a brief introduction to iris recognition and an overview of the chapters in the Second Edition of the Handbook of Iris Recognition.

[1]  Patrick J. Flynn,et al.  Degradation of iris recognition performance due to non-cosmetic prescription contact lenses , 2010, Comput. Vis. Image Underst..

[2]  John Daugman,et al.  IRIS RECOGNITION BORDER-CROSSING SYSTEM IN THE UAE , 2004 .

[3]  Bruce A. Draper,et al.  Overview of the Multiple Biometrics Grand Challenge , 2009, ICB.

[4]  David Zhang,et al.  An Analysis of IrisCode , 2010, IEEE Transactions on Image Processing.

[5]  Arun Ross,et al.  Iris image reconstruction from binary templates: An efficient probabilistic approach based on genetic algorithms , 2013, Comput. Vis. Image Underst..

[6]  Patrick J. Flynn,et al.  Empirical Evidence for Correct Iris Match Score Degradation with Increased Time-Lapse between Gallery and Probe Matches , 2009, ICB.

[7]  J. L. Wayman,et al.  Best practices in testing and reporting performance of biometric devices. , 2002 .

[8]  Adam Czajka.  Influence of Iris Template Aging on Recognition Reliability , 2013, BIOSTEC.

[9]  James R. Matey,et al.  Iris on the Move: Acquisition of Images for Iris Recognition in Less Constrained Environments , 2006, Proceedings of the IEEE.

[10]  David G. Green,et al.  Statistical Behaviour of the GMDH Algorithm , 1988 .

[11]  George W. Quinn,et al.  IREX VI : Temporal Stability of Iris Recognition Accuracy , 2013 .

[12]  Alice J. O'Toole,et al.  FRVT 2006 and ICE 2006 Large-Scale Experimental Results , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  Kevin W. Bowyer,et al.  Experimental evidence of a template aging effect in iris biometrics , 2011, 2011 IEEE Workshop on Applications of Computer Vision (WACV).

[14]  John Daugman,et al.  Demodulation by Complex-Valued Wavelets for Stochastic Pattern Recognition , 2003, Int. J. Wavelets Multiresolution Inf. Process..

[15]  Patrick J. Flynn,et al.  Pupil dilation degrades iris biometric performance , 2009, Comput. Vis. Image Underst..

[16]  George W. Quinn,et al.  IREX I: Performance of Iris Recognition Algorithms on Standard Images | NIST , 2009 .

[17]  Arun Ross,et al.  A study on quality-adjusted impact of time lapse on iris recognition , 2012, Defense + Commercial Sensing.

[18]  Ali M. Al-Khouri,et al.  Iris recognition and the challenge of homeland and border control security in UAE , 2008, Telematics Informatics.

[19]  John Daugman,et al.  New Methods in Iris Recognition , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[20]  Marios Savvides,et al.  How to Generate Spoofed Irises From an Iris Code Template , 2011, IEEE Transactions on Information Forensics and Security.

[21]  Patrick J. Flynn,et al.  Image understanding for iris biometrics: A survey , 2008, Comput. Vis. Image Underst..