Biometric Systems : Technology, Design and Performance Evaluation

Technology, Design and Performance Evaluation

By: James L. Wayman (Editor), Anil K. Jain (Editor), Davide Maltoni (Editor)

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Hardcover | 1 December 2004

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392 Pages

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23.5 x 15.88 x 2.54

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The use of computers to recognize humans from physical and behavioral traits dates back to the digital computer evolution of the 1960s. But even after decades of research and hundreds of major deployments, the field of biometrics remains fresh and exciting as new technologies are developed andoldtechnologiesareimprovedandfieldedinnewapplications.Wor- wide over the past few years,there has been a marked increase in both g- ernment and private sector interest in large-scale biometric deployments for accelerating human-machine processes, efficiently delivering human services, fighting identity fraud and even combating terrorism. The p- pose of this book is to explore the current state of the art in biometrics- tems and it is the system aspect that we have wished to emphasize. By their nature, biometric technologies sit at the exact boundary of the human-machineinterface.Butlikealltechnologies,bythemselvestheycan provide no value until deployed in a system with support hardware, n- work connections, computers, policies and procedures, all tuned together to work withpeople to improve some real business process within a social structure.

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Non-Fiction Science Biology, Life Sciences Computing & I.T.Computer Science Artificial Intelligence Pattern Recognition Education Digital Signal Processing (DSP)

Preface	p. v
An Introduction to Biometric Authentication Systems	p. 1
Introduction	p. 1
A Quick Historical Overview	p. 2
The "Best" Biometric Characteristic	p. 3
The Applications	p. 4
A Taxonomy of Uses	p. 5
A Taxonomy of Application Environments	p. 7
Overt Versus Covert	p. 7
Habituated Versus Non-Habituated	p. 8
Attended Versus Non-Attended	p. 8
Standard Versus Non-Standard Environment	p. 8
Public Versus Private	p. 8
Open Versus Closed	p. 8
Examples of the Classification of Applications	p. 9
A System Model	p. 9
Data Collection	p. 9
Transmission	p. 11
Signal Processing	p. 11
Storage	p. 13
Decision	p. 14
Biometrics and Privacy	p. 14
The Road Ahead	p. 17
References	p. 17
Fingerprint Identification Technology	p. 21
History	p. 21
Early Biometric Efforts	p. 21
Applications of Fingerprints	p. 22
Forensics	p. 22
Genetics	p. 23
Civil and Commercial	p. 23
Government	p. 24
Early Systems	p. 24
Manual Card Files	p. 24
Classification	p. 25
Searching	p. 27
Matching	p. 27
Early Automation Efforts	p. 27
US NBS/NIST Research	p. 28
Royal Canadian Police	p. 28
FBI	p. 28
United Kingdom	p. 29
Japan	p. 30
The Technology	p. 30
Scanning and Digitizing	p. 30
Enhancement	p. 33
Feature Extraction	p. 38
Classification	p. 41
Matching	p. 43
Searching	p. 48
Manual Verification	p. 49
Criminal Applications	p. 49
National Systems	p. 49
Local Systems	p. 51
Interoperability	p. 52
"Daubert" Questions	p. 53
Civil Applications	p. 54
Welfare Fraud Reduction	p. 54
Border Control	p. 55
Driver registration	p. 55
Commercial Applications	p. 56
Miniaturized Sensors	p. 56
Personal Access Protection	p. 57
Banking Security	p. 58
Business-to-Business Transactions	p. 58
References	p. 59
Iris Recognition	p. 63
Introduction	p. 63
Anatomical and Physiological Underpinnings	p. 65
Sensing	p. 68
Iris signature representation and matching	p. 74
Localization	p. 74
Representation	p. 77
Matching	p. 79
Systems and performance	p. 86
Future directions	p. 90
References	p. 92
Face Recognition	p. 97
Introduction	p. 97
Background	p. 98
Face Detection	p. 99
Face Recognition: Representation and Classification	p. 100
Some Representation Techniques and Their Applications to Face Recognition	p. 101
Some Classification Techniques and Their Applications to Face Recognition	p. 103
Kernel-Based Methods and 3D Model-based Methods for Face Recognition	p. 105
Learning the Face Space	p. 106
Evolutionary Pursuit	p. 106
Face Recognition Using Evolutionary Pursuit	p. 108
Conclusion	p. 109
References	p. 110
Elements of Speaker Verification	p. 115
Introduction	p. 115
The Speaker Verification Problem	p. 115
Features and Models	p. 120
Speech Features	p. 120
Speaker Models	p. 121
Additional Methods for Managing Variability	p. 126
Channel Normalization and Modeling	p. 126
Constraining the Text	p. 128
Measuring Performance	p. 129
How Well do These Systems Perform?	p. 131
Alternative Approaches	p. 131
Speech Recognition Approaches	p. 131
Words (and Phonetic Units) Count	p. 132
Models Exploring the Shape of Feature Space	p. 133
Summary	p. 133
References	p. 134
Technology Evaluation of Fingerprint Verification Algorithms	p. 137
Introduction	p. 137
FVC2000 Organization and Algorithms Submission Rules	p. 139
Databases	p. 142
Performance Evaluation	p. 149
Results	p. 151
Organization of FVC2002	p. 155
Conclusions	p. 158
Appendix A	p. 159
Appendix B	p. 159
References	p. 204
Methods for Assessing Progress in Face Recognition	p. 207
Introduction	p. 207
Face Recognition Evaluations	p. 208
Introduction to FERET and FRVT 2000	p. 208
September 1996 FERET Evaluation Protocol	p. 212
Data Sets	p. 215
FERET and FRVT 2000 Results	p. 218
Conclusions Drawn from the FERET Evaluations and FRVT 2000	p. 225
Meta-Analysis	p. 227
Introduction to Meta-Analysis	p. 228
Methodology for Selecting Papers	p. 229
Analysis of Performance Scores - Viewing the Data Through Histograms	p. 230
Evaluation of Experiments with a Baseline	p. 232
Meta-Analysis Conclusions	p. 234
Conclusion	p. 236
Acknowledgements	p. 237
References	p. 237
The NIST speaker recognition evaluation program	p. 241
Introduction	p. 241
NIST Speaker Recognition Evaluation Tasks	p. 242
One-Speaker Detection	p. 243
Two-Speaker Detection	p. 243
Speaker Tracking	p. 243
Speaker Segmentation	p. 244
Data	p. 244
Speaker Training	p. 245
Test Segments	p. 245
Performance Measure	p. 247
Evaluation Results	p. 248
Factors Affecting Detection Performance	p. 249
Duration	p. 250
Pitch	p. 250
Handset Differences	p. 251
Handset Type	p. 252
Landline vs. Cellular	p. 255
Extended Data Evaluation	p. 256
Multimodal Evaluation	p. 258
Future Plans	p. 260
References	p. 261
Large-Scale Identification System Design	p. 263
Introduction	p. 263
Historical Background	p. 263
Large-Scale Identification Systems: Requirements and Basic Features	p. 265
Extrapolation of Accuracy	p. 266
Introduction	p. 266
Key Concepts	p. 268
Method 1: Extrapolation from Experiences	p. 269
Method 2: Identification as a Succession of N Verifications	p. 270
Method 3: Extrapolation with Extreme Value	p. 272
Method 4: Extrapolation when the Distance Can Be Modeled	p. 275
Influence of Classification	p. 276
Conclusion	p. 279
Appendix	p. 281
References	p. 286
Biometric System Integration	p. 289
Understanding, Describing and Documenting the Requirements	p. 289
Choosing the Technology	p. 291
Application Development	p. 294
Integration with Existing System Architecture	p. 296
Templates and Enrollment Management	p. 297
Understanding User Psychology	p. 300
Fine Tuning the System	p. 302
Ongoing Management	p. 305
Related Issues	p. 306
References	p. 309
Biometrics and the US Constitution	p. 311
Introduction	p. 311
Privacy Versus Security; Mankind Versus Machine	p. 311
The Growth of Both Anonymous Public Transactions and the Complexity of Identification	p. 312
Constitutional Concerns	p. 313
Due Process	p. 314
Entitlements and Rights	p. 314
Instrumental and Intrinsic Approaches	p. 315
Constitutional Development: From the Intrinsic to the Instrumental Approach of Procedural Due Process	p. 317
The Enigma of Substantive Due Process	p. 320
Individual Privacy	p. 322
The Basis of an Inferred Right to Privacy	p. 322
Privacy and the Fourth Amendment	p. 323
Privacy and the Fifth Amendment	p. 325
Privacy of Personal Information	p. 326
Conclusions	p. 328
References and Notes	p. 329
Privacy Issues in the Application of Biometrics: a European Perspective	p. 335
Introduction	p. 335
Privacy - from Philosophical Concept to a Human Right	p. 337
The European Personal Data Directive	p. 340
Applying the Directive and National Laws to Biometric Systems	p. 342
Biometric Data as "Personal Data"	p. 343
Biometrics and Sensitive Data	p. 345
Proportionality Principle	p. 346
First Principle Compliance - Fair and Lawful Processing	p. 346
Fourth Principle Compliance - Accuracy	p. 347
Seventh Principle Compliance - Security	p. 347
Eighth Principle Compliance - Transfer to Third Countries	p. 348
Automatic Decision-Making	p. 348
Exemptions	p. 349
Article 8 of the European Human Rights Convention	p. 349
The Role of Privacy-Enhancing Technologies	p. 350
Looking to the Future	p. 351
Social and Psychological Context of the Application of Biometric Methods	p. 353
Conclusions	p. 356
References	p. 356
Index	p. 361
Table of Contents provided by Publisher. All Rights Reserved.

Biometric Systems : Technology, Design and Performance Evaluation

Technology, Design and Performance Evaluation

At a Glance

Hardcover

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