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Advances in Biometrics
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Advances in Biometrics
Editors
Advances in Biometrics
Venu Govindaraju
Sensors, Algorithms and Systems
.Nalini K. Ratha
Hawthorne, New York, USA IBM Thomas J. Watson Research Center
University of Buffalo, New York, USA
British Library Cataloguing in Publication Data
A catalogue record for this book is available from the British Library
Library of Congress Control Number: 2007929188
Printed on acid-free paper
© Springer-Verlag London Limited 2008
springer.com Springer Science+Business Media
Whilst we have made considerable efforts to contact all holders of copyright material contained in this book, we have failed to locate some of these. Should holders wish to contact the Publisher, we will be happy to come to some arrangement with them. Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case
Agency. Enquiries concerning reproduction outside those terms should be sent to the publishers. of reprographic reproduction in accordance with the terms of licences issued by the Copyright Licensing
specific statement, that such names are exempt from the relevant laws and regulations and therefore free for general use. The publisher makes no representation, express or implied, with regard to the accuracy of the information contained in this book and cannot accept any legal responsibility or liability for any errors or omissions that may be made.
9 8 7 6 5 4 3 2 1
Venu Govindaraju, BTech, MS, PhD
ISBN: 978-1-84628-920-0 e-ISBN: 978-1-84628-921-7
The use of registered names, trademarks, etc., in this publication does not imply, even in the absence of a
Department of Computer Science and Engineering Nalini K. Ratha, BTech, MTech, PhD
Preface
Overview and Goals
Recognizing people based on their physiological or behavioral characteristicsis the main focus of the science of biometrics. With the ever-increasing needfor secure and reliable human identification methods in a highly security-conscious society spurred by recent events around the world, biometrics hassurged from an interesting application of pattern-recognition techniques toa vibrant mainstream research topic over the last decade. The exponentialgrowth of research in this area focuses on many challenging research prob-lems including evaluating new biometrics techniques, significantly improvingaccuracy in many existing biometrics, new sensing techniques, and large-scalesystem design issues. Biometrics technology relies on advances in many alliedareas including pattern recognition, computer vision, signal/image processing,statistics, electrical engineering, computer science, and machine learning. Sev-eral books, conferences, and special issues of journals have been published andmany are in the active pipeline covering these advanced research topics.
Most of the published work assumes the biometric signal has been reliablyacquired by the sensors and the task is one of controlling false match and falserejection rates. Thus, the focus and thrust of many researchers have been onpattern recognition and machine-learning algorithms in recognizing biometricssignals. However, the emphasis on the sensors themselves, which are criticalin capturing high-quality signals, has been largely missing from the researchdiscourse. We have endeavored to remedy this by including several chaptersrelating to the sensors for the various biometric modalities. This is perhapsthe first book to provide a comprehensive treatment of the topic. Althoughcovering the sensing aspect of biometrics at length, we are also equally excitedabout new algorithmic advances fundamentally changing the course for someof the leading and popular biometrics modalities as well as new modalitiesthat may hold a new future. There has also been interest at the systems levelboth from a human factors point of view and the perspective of networking,
vi Preface
databases, privacy, and antispoofing. Our goal in designing this book has beenprimarily based on covering many recent advances made in these three keyareas: sensors, algorithms, and systems.
Organization and Features
The chapters in this book have been authored by the leading authorities inthe field making this book a unique blueprint of the advances being made onall frontiers of biometrics with coverage of the entire gamut of topics includ-ing data acquisition, pattern-matching algorithms, and issues such as stan-dards, security, networks, and databases that have an impact at the systemlevel. Accordingly, the book has been organized under three roughly clus-tered parts: Part I pertains to sensors, Part II is about advances in biometricmatching algorithms, and Part III deals with issues at the systems level. Chap-ters within any one cluster are self-explanatory and do not depend on priorchapters.
We have emphasized the advances and cutting-edge technologies in eachof the parts with the understanding that readers have other options for look-ing up matching algorithms for commonly used modalities such as fingerprintand face recognition. Our focus has been on the newer modalities, be it theuse of infrared imaging for measuring the distinguishing features in vascularstructures, multispectral imaging to ensure liveness, or iris on the move for un-obtrusive identification in surveillance scenarios. With respect to fingerprints,we have devoted chapters in Part I to touchless image capture, ultrasonic imag-ing, and swipe methods.
Part II is divided roughly equally between behavioral (handwriting, voice)and physical biometrics (face, iris) with an additional chapter on a strikinglynovel modality in headprint biometrics.
Readers will also find the inclusion of the chapter on standards in Part IIIto be an extremely convenient reference.
Target Audience
The primary intended audience for this book is the research community bothfrom industry and academia as reflected by the authorship of the chapterswhere we have roughly equal participation from both. The insight providedby the industry chapters is invaluable as it provides the perspective of actualworking systems. We anticipate the book to be a ready reference on the stateof the art in biometric research.
The secondary audience is graduate students taking an advanced researchtopics course on their way to a doctoral dissertation. This will be well suited forstudents specializing in biometrics, image processing, and machine learning as
Preface vii
it can provide ideal application testbeds to test their algorithms. The bench-marks provided for several modalities in Part II should prove to be useful aswell.
Acknowledgments
We are extremely thankful to all the chapter authors who have contributed tomake this book a unique resource for all researchers. The 24 chapters are thecombined effort of 53 authors. We have truly enjoyed interacting with themat all stages of book preparation: concept, drafts, proofs, and finalization. Wewould also like to thank Achint Thomas for helping with the FTP submissionsof the manuscripts and proofreading. Last, but not least, we are grateful toSpringer for constantly driving us for timely completion of the tasks on ourend.
Hawthorne, New York Nalini K. RathaBuffalo, New York Venu GovindarajuApril 2007
Contents
Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xvii
Part I Sensors
1 Multispectral Fingerprint Image Acquisition . . . . . . . . . . . . . . . . 3Robert K. Rowe, Kristin Adair Nixon, and Paul W. Butler
2 Touchless Fingerprinting Technology . . . . . . . . . . . . . . . . . . . . . . . . 25Geppy Parziale
3 A Single-Line AC Capacitive Fingerprint Swipe Sensor . . . . . . 49Sigmund Clausen
4 Ultrasonic Fingerprint Sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63John K. Schneider
5 Palm Vein Authentication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75Masaki Watanabe
6 Finger Vein Authentication Technology andFinancial Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89Mitsutoshi Himaga and Katsuhiro Kou
7 Iris Recognition in Less Constrained Environments . . . . . . . . . . 107James R. Matey, David Ackerman, James Bergen,and Michael Tinker
x Contents
8 Ocular Biometrics: Simultaneous Capture andAnalysis of the Retina and Iris . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133David Usher, Yasunari Tosa, and Marc Friedman
9 Face Recognition Beyond the Visible Spectrum . . . . . . . . . . . . . . 157Pradeep Buddharaju, Ioannis Pavlidis, and Chinmay Manohar
Part II Algorithms
10 Voice-Based Speaker Recognition Combining Acousticand Stylistic Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183Sachin S. Kajarekar, Luciana Ferrer, Andreas Stolcke,and Elizabeth Shriberg
11 Conversational Biometrics:A Probabilistic View . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203Jason Pelecanos, Jirı Navratil, and Ganesh N. Ramaswamy
12 Function-Based Online Signature Verification . . . . . . . . . . . . . . . 225Julian Fierrez and Javier Ortega-Garcia
13 Writer Identification and Verification . . . . . . . . . . . . . . . . . . . . . . . 247Lambert Schomaker
14 Improved Iris Recognition Using Probabilistic Informationfrom Correlation Filters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265Jason Thornton, Marios Savvides, and B.V.K. Vijaya Kumar
15 Headprint-Based Human Recognition . . . . . . . . . . . . . . . . . . . . . . 287Hrishikesh Aradhye, Martin Fischler, Robert Bolles, and Gregory Myers
16 Pose and Illumination Issues in Face-and Gait-Based Identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 307Rama Chellappa and Gaurav Aggarwal
17 SVDD-Based Face Reconstructionin Degraded Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323Sang-Woong Lee and Seong-Whan Lee
18 Strategies for Improving Face Recognitionfrom Video . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339Deborah Thomas, Kevin W. Bowyer, and Patrick J. Flynn
19 Large-Population Face Recognition (LPFR)Using Correlation Filters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 363Chunyan Xie and B.V.K. Vijaya Kumar
Contents xi
Part III Systems
20 Fingerprint Synthesis and Spoof Detection . . . . . . . . . . . . . . . . . 385Annalisa Franco and Davide Maltoni
21 Match-on-Card for Secure andScalable Biometric Authentication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 407Christer Bergman
22 Privacy and Security Enhancements in Biometrics . . . . . . . . . . 423Terrance E. Boult and Robert Woodworth
23 Adaptive Biometric Systems That CanImprove with Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 447Fabio Roli, Luca Didaci, and Gian Luca Marcialis
24 Biometrics Standards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 473Farzin Deravi
Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 491
Contributors
David AckermanSarnoff Corporation,Princeton, NJ 08543-5300, USA,[email protected]
Gaurav AggarwalCenter for Automation Research andDepartment of Computer Science,University of Maryland,College Park, MD 20742, USA,[email protected]
Hrishikesh AradhyeSRI International,333 Ravenswood Avenue,Menlo Park, CA 94025, USA,[email protected]
James BergenSarnoff Corporation,Princeton, NJ 08543-5300, USA,[email protected]
Christer BergmanPrecise Biometrics AB,Lund, Sweden,[email protected]
Robert BollesSRI International,333 Ravenswood Avenue,Menlo Park, CA 94025, USA,[email protected]
Terrance E. BoultDepartment of Computer Science,University of Colorado at ColoradoSprings, EAS#3, 1420,Austin Bluffs Parkway,Colorado Springs,CO 80933-7150,[email protected],andSecurics, Inc, Colorado Springs,CO, USA
Kevin W. BowyerDepartment of ComputerScience and Engineering,University of Notre Dame,Notre Dame, IN, USA,[email protected]
Pradeep BuddharajuDepartment of Computer Science,University of Houston, 4800 CallhounRoad, Houston, TX 77204, USA,[email protected]
Paul W. ButlerLumidigm, Inc.,801 University Blvd. SE,Suite 302,Albuquerque, NM 87106, USA,[email protected]
xiv Contributors
Rama ChellappaCenter for Automation Research,and Department of Electricaland Computer Engineering,University of Maryland,College Park, MD 20742, USA,[email protected]
Sigmund ClausenIdex ASA, Snarøya,Norway,[email protected]
Farzin DeraviDepartment of Electronics,University of Kent, UK,[email protected]
Luca DidaciDepartment of Electricaland Electronic Engineering,University of Cagliari Piazza d’Armi,I-09123 Cagliari, Italy,[email protected]
Luciana FerrerDepartment ofElectrical Engineering,Stanford University, CA, USA,[email protected]
Julian FierrezATVS–Biometric Recognition Group,Escuela Politecnica Superior,Universidad Autonoma de Madrid,Spain,[email protected]
Martin FischlerSRI International,333 Ravenswood Avenue,Menlo Park, CA 94025, USA,[email protected]
Patrick J. FlynnDepartment of ComputerScience and Engineering,University of Notre Dame,Notre Dame, IN, USA,[email protected]
Annalisa FrancoC.d.L. Scienze dell’Informazione,University of Bologna,Via Sacchi 3, Cesena,Italy,[email protected]
Marc FriedmanRetica Systems Inc, Waltham,Massachusetts, USA,[email protected]
Mitsutoshi HimagaR&D Division, Hitachi-OmronTerminal Solutions, Corp.,Owari-asahi, Aichi, Japan,mitsutoshi [email protected]
Sachin S. KajarekarSRI International,Menlo Park, CA, USA,[email protected]
Katsuhiro KouAutomated Teller Machine SystemsGroup, Hitachi-Omron TerminalSolutions, Corp., Shinagawa-ku,Tokyo, Japan,katsuhiro [email protected]
B.V. K. Vijaya KumarDepartment of Electricaland Computer Engineering,Carnegie Mellon University,Pittsburgh, Pennsylvania, USA,[email protected]
Sang-Woong LeeKorea University, Anam-dongSeongbuk-ku, Seoul 136-713, Korea,[email protected]
Contributors xv
Seong-Whan LeeKorea University, Anam-dongSeongbuk-ku, Seoul 136-713, Korea,[email protected]
Davide MaltoniScienze dell’Informazione,Universita di Bologna,Via Sacchi 3, 47023Cesena (FO), Italy,[email protected]
Chinmay ManoharDepartment of Internal Medicine,Endocrine Research Unit,Division of Endocrinology,Mayo Clinic, Rochester,MN 55905, USA,[email protected]
Gian Luca MarcialisDepartment of Electricaland Electronic Engineering,University of Cagliari Piazza d’Armi,I-09123 Cagliari, Italy,[email protected]
James R. MateySarnoff Corporation,Princeton, NJ 08543-5300, USA,[email protected]
Gregory MyersSRI International, 333 RavenswoodAvenue, Menlo Park,CA 94025, USA,[email protected]
Jirı NavratilConversational Biometrics Group,IBM T.J. Watson Research Center,1101 Kitchawan Road, YorktownHeights, NY 10598, USA,[email protected]
Kristin Adair NixonLumidigm, Inc.,Suite 302,801 University Blvd. SE,Albuquerque, NM 87106, USA,[email protected]
Javier Ortega-GarciaATVS–Biometric Recognition Group,Escuela Politecnica Superior,Universidad Autonoma de Madrid,Spain,[email protected]
Geppy ParzialeCogent Systems, Inc.,South Pasadena, CA, USA,[email protected]
Ioannis PavlidisDepartment of Computer Science,University of Houston, 4800 CallhounRoad, Houston, TX 77204, USA,[email protected]
Jason PelecanosConversational BiometricsGroup, IBM T.J. Watson ResearchCenter, 1101 Kitchawan Road,Yorktown Heights, NY 10598, USA,[email protected]
Ganesh N. RamaswamyConversational Biometrics Group,IBM T.J. Watson Research Center,1101 Kitchawan Road,Yorktown Heights, NY 10598, USA,[email protected]
Fabio RoliDepartment of Electricaland Electronic Engineering,University of Cagliari Piazza d’Armi,I-09123 Cagliari, Italy,[email protected]
xvi Contributors
Robert K. RoweLumidigm, Inc.,Suite 302,801 University Blvd. SE,Albuquerque, NM 87106, USA,[email protected]
Marios SavvidesDepartment of Electricaland Computer Engineering,Carnegie Mellon University,Pittsburgh, Pennsylvania, USA,[email protected]
John K. SchneiderUltra-Scan Corporation,Amherst, New York, USA,[email protected]
Lambert SchomakerDepartment of Artificial Intelligence,University of Groningen,Grote Kruisstr. 2/1, 9712 TS,Groningen, The Netherlands,[email protected]
Elizabeth ShribergInternational ComputerScience Institute,Berkeley, CA, USA,[email protected]
Andreas StolckeSRI International,Menlo Park,andInternational ComputerScience Institute,Berkeley, CA, USA,[email protected]
Deborah ThomasDepartment of ComputerScience and Engineering,University of Notre Dame,Notre Dame, IN, USA,[email protected]
Jason ThorntonDepartment of Electricaland Computer Engineering,Carnegie Mellon University,Pittsburgh, Pennsylvania, USA,[email protected]
Michael TinkerSarnoff Corporation,Princeton, NJ 08543-5300, USA,[email protected]
Yasunari TosaRetica Systems Inc.,Waltham, Massachusetts, USA,[email protected]
David UsherRetica Systems Inc.,Waltham, Massachusetts, USA,[email protected]
Masaki WatanabeFujitsu Laboratories Ltd.,Kawasaki, Japan,[email protected]
Robert WoodworthSecurics, Inc., Colorado Springs,CO, USA,[email protected]
Chunyan XieDepartment of Electricaland Computer Engineering,Carnegie Mellon University,Pittsburgh, PA, USA,[email protected]
Introduction
This book has 24 chapters and is divided into three parts: sensors, algorithms,and systems. There are nine chapters on sensors covering a wide range oftraditional to novel data acquisition mechanisms, ten chapters on advancedalgorithms for matching, and five chapters on system-level aspects such asstandards and smartcards.
Part I: Sensors
Research has shown that biometric image quality is one of the most signifi-cant variables affecting biometric system accuracy and performance. We haveincluded four chapters on the latest developments in fingerprint sensors cov-ering multispectral imaging, touchless sensors, swipe sensors, and ultrasoundcapture. The chapter on multispectral imaging describes the capture of boththe surface and subsurface features of the skin in order to generate a compos-ite fingerprint image that has the added advantage of confirming “liveness”of human skin. The chapter on touchless fingerprint sensing presents a newapproach that does not deform the skin during the capture, thus ensuringrepeatability of measurements. The advantages and disadvantages with re-spect to legacy technology are highlighted. The chapter on swipe sensors isessentially about an image reconstruction algorithm that accounts for varyingswiping speeds and directions. Finally, the chapter on ultrasonic imaging forlivescan fingerprint applications describes how it is more tolerant to humidity,extreme temperatures, and ambient light when compared to optical scanners.
Measurement of vascular structures has been gaining popularity in mission-critical applications such as financial transactions because of the accuracyrendered and, more importantly, because of their robustness against spoofattacks. Two chapters on this topic have been included to provide an insightinto this novel biometrics, both at the palm level as well as the finger level.The chapter on iris recognition systems describes image capture from movingsubjects and at greater distances than have been available in the COTS.
xviii Introduction
The retina and iris are occular biometrics with uncorrelated complemen-tary information and anatomical proximity allowing simultaneous capture bya single device. We have included a chapter that describes their integrationinto a single biometric solution. The final chapter in the sensors section is onthe use of the facial vascular network, how it is highly characteristic of theindividual, and how it can be unobtrusively captured through thermal imag-ing. The efficacy of this information for identity recognition is demonstratedby testing on substantial databases.
Part II: Algorithms
This part has two chapters pertaining to voice, two chapters that relate tohandwriting, three chapters on face, and a chapter each on iris and headprint.
The first chapter on voice biometrics describes the general framework of atext-independent speaker verification system. It extracts short-term spectralfeatures that implicitly capture the anatomy of the vocal apparatus and arecomplementary to spectral acoustic features. The other voice-related chapterintroduces conversational biometrics, which is the combination of acousticvoicematching (traditional speaker verification)withother conversation-relatedinformation sources (such as knowledge) to perform identity verification.
The chapters on handwriting are on signature verification and writer iden-tification. Readers will find the evaluation experiments to be an extremelyuseful benchmark in signature verification. The chapter reports results on asubcorpus of the MCYT biometric database comprising more than 7000 sig-natures from 145 subjects with comparisons to results reported at the FirstInternational Signature Verification Competition (SVC, 2004). The chapteron writer identification describes a methodology of combining textural, allo-graphic, and placement features to improve accuracy.
The chapter on iris recognition asserts that matching performance becomesmore robust when images are aligned with a flexible deformation model, usingdistortion-tolerant similarity cues. Again, useful benchmarks are provided bycomparisons to the standard iris matching algorithm on the NIST Iris Chal-lenge Evaluation (ICE, 2006).
Headprint-based recognition is a novel and unobtrusive biometric that isparticularly useful in surveillance applications. The chapter presents new al-gorithms for separation of hair area from the background in overhead imageryand extraction of novel features that characterize the color and texture of hair.The more traditional biometrics used in surveillance are face and gait. How-ever, current algorithms perform poorly when illumination conditions and poseare changing. We have therefore included one chapter that focuses on uncon-trolled realistic scenarios, and another that proposes a new method of extend-ing SVDD (Support Vector Data Description) to deal with noisy and degradedframes in surveillance videos. Face recognition from video also allows the use ofmultiple images available per subject. This strategy is described in a chapter
Introduction xix
where the emphasis is on selection of frames from the video sequences basedon quality and difference from each other. Four different approaches have beencompared on a video dataset collected by the University of Notre Dame. Thelast chapter on face biometrics deals with matching against large populationsin real-time. This chapter introduces correlation pattern-recognition-based al-gorithms for the purpose.
Part III: Systems
There are five chapters in this part dealing with smartcards, privacy andsecurity issues, methods for system-level improvements, and standards.
It has often been believed that the features derived from a biometric signalare not helpful in getting much information about the original biometrics andhave been thought of loosely as a one-way hash of the biometrics. The chapteron fingerprint image synthesis disproves this notion by reconstructing the fin-gerprint image from its well-known industry standard template often used asa basis for information interchange between algorithms from multiple vendors.The results shown should convince the reader that the templates can be used toattack a biometrics system with these reconstructed images. A related advancecovered in this chapter deals with detecting fake fingers based on odor sensing.
Whether it is a large-scale database such as US-VISIT or a small bank ofbiometrics stored on a server for logical access in an office, the solutions arebased on insecure networks that are vulnerable to cyberattacks. The chapteron smartcards describes technology that eliminates the need for the data-base by both storing and processing biometric data directly on the card, thusproviding security, privacy, dynamic flexibility, and scalability. Security andprivacy are also the focus of the chapter on BiotopesTM, which is essentiallya method to transform the original biometric signature into an alternativerevocable form (the Biotope) that protects privacy while supporting a robustdistance metric necessary for approximate matching.
The chapter on adaptive biometric systems describes a method of improv-ing performance by training on the fly. The unlabelled data that a systemexamines in test scenarios can be analyzed for parameters such as image qual-ity (as they are sensor- and session-dependent), which can in turn be usedadaptively by the recognition algorithms.
The final chapter of the book addresses the history, current status, andfuture developments of standardization efforts in the field of biometrics. Thefocus is on the activities of ISO’s SC37 subcommittee dealing with biometricstandardization.
References
SVC: http://www.cs.ust.hk/svc2004/ICE: http://iris.nist.gov/ICE/
