A study on quality-adjusted impact of time lapse on iris recognition

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 8371, Issue , 2012, Pages

  Sazonova, Nadezhda ^a   Hua, Fang ^b   Liu, Xuan ^c   Remus, Jeremiah ^b   Ross, Arun ^d   Hornak, Lawrence ^d   Schuckers, Stephanie ^b  

^a UNIVERSITY OF ALABAMA   (United States)

^b Clarkson University   (United States)

^c UNIVERSITY OF FLORIDA   (United States)

^d WEST VIRGINIA UNIVERSITY   (United States)

Author keywords

Iris quality measurement; Iris recognition performance; Robust regression; Statistical analysis; Time lapse

Indexed keywords

AGING EFFECTS; BIOMETRIC FEATURES; CLARKSON UNIVERSITY; COMMERCIAL SOFTWARE; HUMAN IRIS; IRIS IMAGES; IRIS RECOGNITION; IRIS RECOGNITION SYSTEMS; LEGACY DATABASE; LOCAL CONTRAST; MATCH SCORE; PREDICTION SCHEMES; QUALITY FACTORS; QUALITY MEASUREMENTS; QUALITY METRICS; REGRESSION MODEL; ROBUST REGRESSIONS; TIME LAPSE;

DEGRADATION; ENVIRONMENTAL ENGINEERING; IMAGE MATCHING; REGRESSION ANALYSIS; STATISTICAL METHODS; TECHNOLOGY;

BIOMETRICS;

EID: 84863905116     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.919642     Document Type: Conference Paper

References (13)

1. J. Daugman, "How iris recognition works, " IEEE Transactions on Circuits and Systems for Video Technology, vol. 14, no. 1, 21-30 (2004).
2. K. Miyazawa, K. Ito, T. Aoki, K. Kobayashi, and H. Nakajima, "An Effective Approach for Iris Recognition Using Phase- Based Image Matching, " IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, no. 10, 1741-1756 ( 2008).
3. P. Tome-Gonzalez, F. Alonso-Fernandez, and J. Ortega-Garcia, "On the Effects of Time Variability in Iris Recognition, " in 2nd IEEE International Conference on Biometrics: Theory, Applications and Systems, 2008. BTAS 2008, 1-6 (2008).
4. S. Baker, K. Bowyer, and P. Flynn, "Empirical Evidence for Correct Iris Match Score Degradation with Increased Time- Lapse between Gallery and Probe Matches, " in Advances in Biometrics, vol. 5558, Springer Berlin/Heidelberg, 1170- 1179(2009).
5. S. P. Fenker and K. W. Bowyer, "Experimental evidence of a template aging effect in iris biometrics, " in 2011 IEEE Workshop on Applications of Computer Vision (WACV), 232-239 (2011).
6. P. Grother and E. Tabassi, "Performance of Biometric Quality Measures, " IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29, no. 4, 531-543 (2007).
7. E. Tabassi, P. Grother, and W. Salamon, "IREX II - IQCE Iris Quality Calibration and Evaluation: Performance of Iris Image Quality Assessment Algorithms, " NIST Interagency Report 7820, (2011).
8. N. Sazonova, S. Schuckers, P. Johnson, P. Lopez-Meyer, E. Sazonov, and L. Hornak, "Impact of out-of-focus blur on iris recognition, " in SPIE Defense, Security, and Sensing, 80291S-80291S-8 (2011).
9. F. Hua, P. Johnson, N. Sazonova, P. Lopez-Meyer, S. Schuckers, and A. Ross, "Impact of Out-of-focus Blur on Face Recognition Performance Based on Modular Transfer Function, " to be presented in The 5th IAPR International Conference on Biometrics, (2012).
10. E. Peli, "Contrast in complex images, " J. Opt. Soc. Am. A, vol. 7, no. 10, 2032-2040 (1990).
11. J. Wan, X. He, and P. Shi, "An Iris Image Quality Assessment Method Based on Laplacian of Gaussian Operation, " in IAPR Conference on Machine Vision Applications, (2007).
12. L. Masek, "Recognition of Human Iris Patterns for Biometric Identification, " (2003).
13. "Multimodal Biometric Dataset Collection, Clarkson University, " Center for Identification Technology Research (CITeR). http://www.citer.wvu.edu/multimodal-biometric-dataset-collection-clarksonuniv- release2.