Introduction to the Handbook of Iris Recognition -- A Survey of Iris Biometrics Research: 2008-2010 -- Optics of Iris Imaging Systems -- Standard Iris Storage Formats -- Iris Quality Metrics for Adaptive Authentication -- Quality and Demographic Investigation of ICE 2006 -- Methods for Iris Segmentation -- Iris Recognition with Taylor Expansion Features -- Application of Correlation Filters for Iris Recognition -- Introduction to the IrisCode Theory -- Robust and Secure Iris Recognition -- Multispectral Iris Fusion and Cross-Spectrum Matching -- Iris Segmentation for Challenging Periocular Images -- Periocular Recognition from Low Quality Iris Images -- Unconstrained Iris Recognition in Visible Wavelengths -- Design Decisions for an Iris Recognition SDK -- Fusion of Face and Iris Biometrics -- A Theoretical Model for Describing Iris Dynamics -- Iris Liveness Detection by Modeling Dynamic Pupil Features -- Iris Image Reconstruction from Binary Templates -- Off-Angle Iris Correction Methods -- Ophthalmic Disorder Menagerie and Iris Recognition -- Template Aging in Iris Biometrics.

The definitive work on iris recognition technology, this comprehensive handbook presents a broad overview of the state of the art in this exciting and rapidly evolving field. Revised and updated from the highly-successful original, this second edition has also been considerably expanded in scope and content, featuring four completely new chapters. Topics and features: With a Foreword by the "father of iris recognition," Professor John Daugman of Cambridge University Provides authoritative insights from an international selection of preeminent researchers with experience in sectors of government, industry, and academia Reviews issues covering the full spectrum of the iris recognition process, from acquisition to encoding Presents surveys of topical areas, and discusses the frontiers of iris research, including cross-wavelength matching, iris template aging, and anti-spoofing Describes open source software for the iris recognition pipeline and datasets of iris images Includes new content on liveness detection, correcting off-angle iris images, subjects with eye conditions, and implementing software systems for iris recognition This essential text/reference is an ideal resource for anyone wishing to improve their understanding of iris recognition technology, be they practitioners in industry, managers and executives, or researchers searching for new viewpoints and ideas. Dr. Kevin W. Bowyer is the Schubmehl-Prein Family Professor and Chair of the Department of Computer Science and Engineering at the University of Notre Dame, IN, USA. Dr. Mark J. Burge is a Scientist at the non-profit Noblis Corporation, Falls Church, VA, USA, and Visiting Professor at the US Naval Academy, Annapolis, MD, USA. His other publications include the Springer textbook Digital Image Processing - An Algorithmic Introduction Using Java.