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Unconstrained Iris Recognition in Visible Wavelengths

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Handbook of Iris Recognition

Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

Abstract

One of the most challenging goals in biometrics research is the development of recognition systems to work in unconstrained environments and without assuming the subjects’ willingness to be recognized. This has led to the concept of noncooperative recognition, which broaden the application of biometrics to forensics/criminal seek domains. In this scope, one active research topic seeks to use as main trait the ocular region acquired at visible wavelengths, from moving targets and large distances. Under these conditions, performing reliable recognition is extremely difficult, because such real-world data have features that are notoriously different from those obtained in the classical constrained setups of currently deployed recognition systems. This chapter discusses the feasibility of iris/ocular biometric recognition: it starts by comparing the main properties of near-infrared and visible wavelength ocular data, and stresses the main difficulties behind the accurate segmentation of all components in the eye vicinity. Next, it summarizes the most relevant research conducted in the scope of visible wavelength iris recognition and relates it to the concept of periocular recognition, which is an attempt to augment classes separability by using—apart from the iris—information from the surroundings of the eye. Finally, the current challenges in this topic and some directions for further research are discussed.

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Notes

  1. 1.

    http://socia-lab.di.ubi.pt.

  2. 2.

    http://www.smartsensors.co.uk/products/iris-database/32-000-full-set/.

  3. 3.

    http://biometrics.idealtest.org/.

  4. 4.

    http://www.sciencedirect.com/science/journal/02628856/28/2.

  5. 5.

    http://www.sciencedirect.com/science/journal/01678655/33/8.

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Acknowledgments

The financial support given by “IT: Instituto de Telecomunicações” in the scope of the UID/EEA/50008/2013 project is acknowledged.

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  1. IT: Instituto de Telecomunicações, University of Beira Interior, Covilhã, Portugal

    Hugo Proença

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    Kevin W. Bowyer

  2. Noblis, Inc., Washington, District of Columbia, USA

    Mark J. Burge

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Proença, H. (2016). Unconstrained Iris Recognition in Visible Wavelengths. In: Bowyer, K., Burge, M. (eds) Handbook of Iris Recognition. Advances in Computer Vision and Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-4471-6784-6_15

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