A Multialgorithm Analysis of Three Iris Biometric Sensors

The issue of interoperability between iris sensors is an important topic in large-scale and long-term applications of iris biometric systems. This work compares three commercially available iris sensors and three iris matching systems and investigates the impact of cross-sensor matching on system performance in comparison to single-sensor performance. Several factors which may impact single-sensor and cross-sensor performance are analyzed, including changes in the acquisition environment and differences in dilation ratio between iris images. The sensors are evaluated using three different iris matching algorithms, and conclusions are drawn regarding the interaction between the sensors and the matching algorithm in both the cross-sensor and single-sensor scenarios. Finally, the relative performances of the three sensors are compared.

[1]  B. Stanton,et al.  Biometric Systematic Uncertainty and the User , 2007, 2007 First IEEE International Conference on Biometrics: Theory, Applications, and Systems.

[2]  Patrick J. Flynn,et al.  A cross-sensor evaluation of three commercial iris cameras for iris biometrics , 2011, CVPR 2011 WORKSHOPS.

[3]  Douglas A. Reynolds,et al.  The NIST speaker recognition evaluation - Overview, methodology, systems, results, perspective , 2000, Speech Commun..

[4]  Julian Fiérrez,et al.  Sensor Interoperability and Fusion in Signature Verification: A Case Study Using Tablet PC , 2005, IWBRS.

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

[6]  Stephanie Schuckers,et al.  Quality in face and iris research ensemble (Q-FIRE) , 2010, 2010 Fourth IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS).

[7]  K. Bowyer,et al.  The Importance of Small Pupils: A Study of How Pupil Dilation Affects Iris Biometrics , 2008, 2008 IEEE Second International Conference on Biometrics: Theory, Applications and Systems.

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

[9]  P. Jonathon Phillips,et al.  Meta-Analysis of Third-Party Evaluations of Iris Recognition , 2007, 2007 First IEEE International Conference on Biometrics: Theory, Applications, and Systems.

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

[11]  Alvin F. Martin,et al.  The NIST speaker recognition evaluation program , 2005 .

[12]  Arun Ross,et al.  Biometric Sensor Interoperability: A Case Study in Fingerprints , 2004, ECCV Workshop BioAW.

[13]  Yingzi Eliza Du.  Review of iris recognition: cameras, systems, and their applications , 2006 .

[14]  Julian Fiérrez,et al.  Quality Measures in Biometric Systems , 2012, IEEE Security & Privacy.

[15]  Kevin W. Bowyer,et al.  Dilation aware multi-image enrollment for iris biometrics , 2011, 2011 International Joint Conference on Biometrics (IJCB).

[16]  Andreas Uhl,et al.  Incremental iris recognition: A single-algorithm serial fusion strategy to optimize time complexity , 2010, 2010 Fourth IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS).

[17]  Raghu N. Kacker,et al.  Measures, Uncertainties, and Significance Test in Operational ROC Analysis , 2011, Journal of research of the National Institute of Standards and Technology.

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

[19]  Patrick J. Flynn,et al.  Factors that degrade the match distribution in iris biometrics , 2009, Identity in the Information Society.

[20]  Stephen J. Elliott,et al.  The Human–Biometric-Sensor Interaction Evaluation Method: Biometric Performance and Usability Measurements , 2010, IEEE Transactions on Instrumentation and Measurement.

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