Abstract
Iris biometric entails using the patterns on the iris as a biometric for personal authentication. It has additional benefits over contact-based biometrics such as fingerprints and hand geometry. However, iris biometric often suffers from the following three challenges: ability to handle unconstrained acquisition, privacy enhancement without compromising security, and robust matching. This chapter discusses a unified framework based on sparse representations and random projections that can address these issues simultaneously. Furthermore, recognition from iris videos as well as generation of cancelable iris templates for enhancing the privacy and security is also discussed.
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Acknowledgments
This work was partially supported by a MURI grant N00014-08-1-0638 from the Office of Naval Research.
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Pillai, J.K., Patel, V., Chellappa, R., Ratha, N. (2016). Robust and Secure Iris Recognition. 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_11
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