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Handbook of Vascular Biometrics

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Cover of 'Handbook of Vascular Biometrics'

Table of Contents

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    Book Overview
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    Chapter 1 State of the Art in Vascular Biometrics
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    Chapter 2 A High-Quality Finger Vein Dataset Collected Using a Custom-Designed Capture Device
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    Chapter 3 OpenVein—An Open-Source Modular Multipurpose Finger Vein Scanner Design
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    Chapter 4 An Available Open-Source Vein Recognition Framework
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    Chapter 5 Use Case of Palm Vein Authentication
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    Chapter 6 Evolution of Finger Vein Biometric Devices in Terms of Usability
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    Chapter 7 Towards Understanding Acquisition Conditions Influencing Finger Vein Recognition
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    Chapter 8 Improved CNN-Segmentation-Based Finger Vein Recognition Using Automatically Generated and Fused Training Labels
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    Chapter 9 Efficient Identification in Large-Scale Vein Recognition Systems Using Spectral Minutiae Representations
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    Chapter 10 Different Views on the Finger—Score-Level Fusion in Multi-Perspective Finger Vein Recognition
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    Chapter 11 Retinal Vascular Characteristics
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    Chapter 12 Vascular Biometric Graph Comparison: Theory and Performance
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    Chapter 13 Deep Sclera Segmentation and Recognition
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    Chapter 14 Presentation Attack Detection for Finger Recognition
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    Chapter 15 On the Recognition Performance of BioHash-Protected Finger Vein Templates
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    Chapter 16 Cancellable Biometrics for Finger Vein Recognition—Application in the Feature Domain
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    Chapter 17 Towards Measuring the Amount of Discriminatory Information in Finger Vein Biometric Characteristics Using a Relative Entropy Estimator
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Citations

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Title
Handbook of Vascular Biometrics
Published by
Springer International Publishing, January 2020
DOI 10.1007/978-3-030-27731-4
ISBNs
978-3-03-027730-7, 978-3-03-027731-4
Editors

Andreas Uhl, Christoph Busch, Sébastien Marcel, Raymond Veldhuis

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X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
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 %
Lecturer 3 33%
Student > Master 2 22%
Student > Bachelor 2 22%
Professor 1 11%
Unknown 1 11%
Readers by discipline Count As %
Computer Science 5 56%
Engineering 2 22%
Arts and Humanities 1 11%
Unknown 1 11%