@inbook{e683194b3324472f949bcb1888238ad4,
title = "Robust and Secure Iris Recognition",
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.",
keywords = "Gabor Feature, Iris Image, Random Projection, Restricted Isometry Property, Training Image",
author = "Pillai, \{Jaishanker K.\} and Vishal Patel and Rama Chellappa and Nalini Ratha",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag London 2016.",
year = "2016",
doi = "10.1007/978-1-4471-6784-6\_11",
language = "English",
series = "Advances in Computer Vision and Pattern Recognition",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "247--268",
booktitle = "Advances in Computer Vision and Pattern Recognition",
address = "Germany",
}