Definition
An iris database is a collection of images that contain, at a minimum, the iris region of the eye. The images are typically collected by sensors that operate in the visible spectrum, 380–750 nm, or the near infrared spectrum (NIR), 700–900 nm. The visible spectrum image can be stored as a color image or as an intensity image. The NIR image is always stored as an intensity image.
Introduction
Successful biometric research requires the analysis of human data. For biometric researchers to demonstrate the effectiveness of proposed iris segmentation/recognition techniques and allow fair comparisons with existing methods, publicly available iris databases are required. The perfect iris-image database should be sufficiently large, consist of images collected from a large and heterogeneous group of subjects, and contain images that depict noise factors typically encountered in real world applications. In the following sections, several publicly and freely available iris-image...
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Bibliography
Institute of Automation, Chinese Academy of Science: CASIA v1.0 Iris Image Database, 2008. http://www.nlpr.ia.ac.cn/english/irds/irisdatabase.htm. Accessed 27 Dec, 2008
Phillips, P.J., Bowyer, K.W., Flynn, P.J.: Comment on the CASIA version 1.0 Iris Dataset, IEEE Trans. Pattern Anal. Mach. Intell. 29(10), 1869-1870 (2007)
Institute of Automation, Chinese Academy of Science: CASIA v3.0 Iris Image Database, 2008. http://www.nlpr.ia.ac.cn/english/irds/irisdatabase.htm. Accessed 27 Dec, 2008
Dobeš, M., Machala, L.: UPOL Iris Image Database, 2008. http://phoenix.inf.upol.cz/iris/. Accessed 27 Dec, 2008
Dobeš, M., Machala, L., Tichavský, P., Pospíšil J.: Human Eye Iris Recognition Using the Mutual Information. Optik 115(9), 399–405 (2004)
University of Bath: University of Bath Iris Image Database, 2008. http://www.bath.ac.uk/eleceng/research/sipg/irisweb/index.html. Accessed 27 Dec, 2008
National Institute of Standards and Technology: Iris Challenge Evaluation (ICE), 2008. http://iris.nist.gov/ICE/. Accessed 27 Dec, 2008
Liu, X., Bowyer, K.W., Flynn, P.J.: Iris Recognition and Verification Experiments with Improved Segmentation Method. In Proceedings of Fourth IEEE Workshop on Automatic Identification Advanced Technologies (AutoID). Buffalo, NY, 17–18 October 2005
Multimedia University: MMU1 and MMU2 Iris Image Databases, 2008. http://pesona.mmu.edu.my/~ccteo. Accessed 27 Dec, 2008
West Virginia University: West Virginia University Biometric Dataset Collections, 2008. http://www.csee.wvu.edu/~simonac/CITeR_DB. Accessed 27 Dec, 2008
Ross, A., Crihalmeanu, S., Hornak, L., Schuckers, S.: A Centralized Web-Enabled Multimodal Biometric Database. In Proceedings of the 2004 Biometric Consortium Conference (BCC), Arlington, VA, September 2004
Proença, H., Alexandre, L.: UBIRIS: A Noisy Iris Image Database. In: Proceedings of the 13th International Conference on Image Analysis and Processing (ICIA2005), Vol. 1, pp. 970–977, 2005
SOCIA Lab – University of Beira Interior: UBIRIS.v1 Iris Image Database, 2008. http://iris.di.ubi.pt/ubiris1.html. Accessed 27 Dec, 2008
SOCIA Lab – University of Beira Interior: Noisy Iris Challenge Evaluation – Part I, 2008. http://nice1.di.ubi.pt/
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Woodard, D.L., Ricanek, K. (2009). Iris Databases. In: Li, S.Z., Jain, A. (eds) Encyclopedia of Biometrics. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-73003-5_168
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DOI: https://doi.org/10.1007/978-0-387-73003-5_168
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