Sébastien Marcel & Mark S. Nixon 
Handbook of Biometric Anti-Spoofing [PDF ebook] 
Presentation Attack Detection

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This authoritative and comprehensive handbook is the definitive work on the current state of the art of Biometric Presentation Attack Detection (PAD) – also known as Biometric Anti-Spoofing. Building on the success of the previous, pioneering edition, this thoroughly updated second edition has been considerably expanded to provide even greater coverage of PAD methods, spanning biometrics systems based on face, fingerprint, iris, voice, vein, and signature recognition. New material is also included on major PAD competitions, important databases for research, and on the impact of recent international legislation. Valuable insights are supplied by a selection of leading experts in the field, complete with results from reproducible research, supported by source code and further information available at an associated website.

Topics and features: reviews the latest developments in PAD for fingerprint biometrics, covering optical coherence tomography (OCT) technology, and issues of interoperability; examines methods for PAD in iris recognition systems, and the application of stimulated pupillary light reflex for this purpose; discusses advancements in PAD methods for face recognition-based biometrics, such as research on 3D facial masks and remote photoplethysmography (r PPG); presents a survey of PAD for automatic speaker recognition (ASV), including the use of convolutional neural networks (CNNs), and an overview of relevant databases; describes the results yielded by key competitions on fingerprint liveness detection, iris liveness detection, and software-based face anti-spoofing; provides analyses of PAD in fingervein recognition, online handwritten signature verification, and in biometric technologies on mobile devicesincludes coverage of international standards, the E.U. PSDII and GDPR directives, and on different perspectives on presentation attack evaluation.

This text/reference is essential reading for anyone involved in biometric identity verification, be they students, researchers, practitioners, engineers, or technology consultants. Those new to the field will also benefit from a number of introductory chapters, outlining the basics for the most important biometrics.

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Table des matières

An Introduction to Fingerprint Presentation Attack Detection.- A Study of Hand-Crafted and Naturally-Learned Features for Fingerprint Presentation Attack Detection.- Optical Coherence Tomography for Fingerprint Presentation Attack Detection.- Interoperability among Capture Devices for Fingerprint Presentation Attacks Detection.- Review of Fingerprint Presentation Attack Detection Competitions.- Introduction to Iris Presentation Attack Detection.- Application of Dynamic Features of the Pupil for Iris Presentation Attack Detection.- Review of Iris Presentation Attack Detection Competitions.- Introduction to Face Presentation Attack Detection.- Recent Advances in Face Presentation Attack Detection.- Recent Progress on Face Anti-Spoofing against 3D Mask Attack.- Challenges of Face Presentation Attack Detection in Real Scenarios.- Remote Blood Pulse Analysis for Face Presentation Attack Detection.- Review of Face Presentation Attack Detection Competitions.- Introduction to Voice Presentation Attack Detection and Recent Advances.- A Cross-Database Study of Voice Presentation Attack Detection.- Voice Presentation Attack Detection Using Convolutional Neural Networks.- An Introduction to Vein Presentation Attacks and Detection.- Presentation Attacks in Signature Biometrics: Types and Introduction to Attack Detection.- Evaluation Methodologies for Biometric Presentation Attack Detection.- A Legal Perspective on the Relevance of Biometric Presentation Attack Detection (PAD) for Payment Services Under PSDII and the GDPR.- Standards for Biometric Presentation Attack Detection.

A propos de l’auteur


Dr. Sébastien Marcel is a Senior Researcher and Head of the Biometrics Security and Privacy Group at the Idiap Research Institute, Martigny, Switzerland. He was the Project Coordinator of the EC-funded TABULA RASA (Trusted Biometrics under Spoofing Attacks) and BEAT (Biometrics Evaluation and Testing) projects. He is also the Director of the Swiss Center for Biometrics Research and Testing, a Lecturer at École polytechnique fédérale de Lausanne (EPFL) and Université de Lausanne (UNIL) and Vice-President Conferences of the IEEE Biometrics Council.
Prof. Mark S. Nixon is a Professor of Computer Vision in the School of Electronics and Computer Science at the University of Southampton, UK. He is a co-author of the Springer book Human Identification Based on Gait. He pioneered gait as a biometric, and later joined the pioneers of ear and of soft biometrics. He has worked with many international projects and conferences. He is the current President of the IEEE Biometrics Council, Vice Chair IEEE PSPB, and a member of IAPR TC4 Biometrics.
Prof. Julian Fierrez is an Associate Professor in the School of Engineering (EPS) at the Autonomous University of Madrid (UAM), Spain. He is Vice-Chair of the IAPR Technical Committee on Biometrics (TC4), has participated in large EU projects focused on biometrics since 2003 (most notably BIOSEC, BIOSECURE, TABULA RASA, and BEAT), and has received a number of best paper awards and other prestigious research distinctions, including the IAPR Young Biometrics Investigator Award 2017.
Prof. Nicholas Evans is an Associate Professor at EURECOM, Biot, France where he heads research in Speech and Audio Processing with the Digital Security Department. He led or co-led a number of recent special issues related to anti-spoofing, participated in the EU BIOSECURE, TABULA RASA and OCTAVE projects and is among the co-founders of the ASVspoof initiative and challenge series.

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Langue Anglais ● Format PDF ● Pages 519 ● ISBN 9783319926278 ● Taille du fichier 16.2 MB ● Éditeur Sébastien Marcel & Mark S. Nixon ● Maison d’édition Springer International Publishing ● Lieu Cham ● Pays CH ● Publié 2019 ● Édition 2 ● Téléchargeable 24 mois ● Devise EUR ● ID 6804327 ● Protection contre la copie DRM sociale

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