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Handbook of Iris Recognition

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Cover of 'Handbook of Iris Recognition'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction to the Handbook of Iris Recognition
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    Chapter 2 A Survey of Iris Biometrics Research: 2008–2010
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    Chapter 3 Optics of Iris Imaging Systems
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    Chapter 4 Standard Iris Storage Formats
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    Chapter 5 Iris Quality Metrics for Adaptive Authentication
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    Chapter 6 Quality and Demographic Investigation of ICE 2006
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    Chapter 7 Methods for Iris Segmentation
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    Chapter 8 Iris Recognition with Taylor Expansion Features
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    Chapter 9 Application of Correlation Filters for Iris Recognition
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    Chapter 10 Introduction to the IrisCode Theory
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    Chapter 11 Robust and Secure Iris Recognition
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    Chapter 12 Multispectral Iris Fusion and Cross-Spectrum Matching
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    Chapter 13 Iris Segmentation for Challenging Periocular Images
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    Chapter 14 Periocular Recognition from Low-Quality Iris Images
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    Chapter 15 Unconstrained Iris Recognition in Visible Wavelengths
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    Chapter 16 Design Decisions for an Iris Recognition SDK
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    Chapter 17 Fusion of Face and Iris Biometrics
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    Chapter 18 A Theoretical Model for Describing Iris Dynamics
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    Chapter 19 Iris Liveness Detection by Modeling Dynamic Pupil Features
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    Chapter 20 Iris Image Reconstruction from Binary Templates
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    Chapter 21 Off-Angle Iris Correction Methods
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    Chapter 22 Ophthalmic Disorder Menagerie and Iris Recognition
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    Chapter 23 Template Aging in Iris Biometrics
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Citations

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Title
Handbook of Iris Recognition
Published by
Springer London, January 2016
DOI 10.1007/978-1-4471-6784-6
ISBNs
978-1-4471-6782-2, 978-1-4471-6784-6
Editors

Kevin W. Bowyer, Mark J. Burge

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 22%
Researcher 1 11%
Student > Doctoral Student 1 11%
Student > Postgraduate 1 11%
Unknown 4 44%
Readers by discipline Count As %
Computer Science 5 56%
Unknown 4 44%