Biometric systems : technology, design, and performance evaluation /
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| Imprint: | London : Springer, c2005. |
|---|---|
| Description: | xiv, 370 p. : ill. (some col.) ; 24 cm. |
| Language: | English |
| Subject: | |
| Format: | Print Book |
| URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/5922240 |
Table of Contents:
- Preface
- 1. An Introduction to Biometric Authentication Systems
- 1.1. Introduction
- 1.2. A Quick Historical Overview
- 1.3. The "Best" Biometric Characteristic
- 1.4. The Applications
- 1.5. A Taxonomy of Uses
- 1.6. A Taxonomy of Application Environments
- 1.6.1. Overt Versus Covert
- 1.6.2. Habituated Versus Non-Habituated
- 1.6.3. Attended Versus Non-Attended
- 1.6.4. Standard Versus Non-Standard Environment
- 1.6.5. Public Versus Private
- 1.6.6. Open Versus Closed
- 1.6.7. Examples of the Classification of Applications
- 1.7. A System Model
- 1.7.1. Data Collection
- 1.7.2. Transmission
- 1.7.3. Signal Processing
- 1.7.4. Storage
- 1.7.5. Decision
- 1.8. Biometrics and Privacy
- 1.9. The Road Ahead
- References
- 2. Fingerprint Identification Technology
- 2.1. History
- 2.1.1. Early Biometric Efforts
- 2.2. Applications of Fingerprints
- 2.2.1. Forensics
- 2.2.2. Genetics
- 2.2.3. Civil and Commercial
- 2.2.4. Government
- 2.3. Early Systems
- 2.3.1. Manual Card Files
- 2.3.2. Classification
- 2.3.3. Searching
- 2.3.4. Matching
- 2.4. Early Automation Efforts
- 2.4.1. US NBS/NIST Research
- 2.4.2. Royal Canadian Police
- 2.4.3. FBI
- 2.4.4. United Kingdom
- 2.4.5. Japan
- 2.5. The Technology
- 2.5.1. Scanning and Digitizing
- 2.5.2. Enhancement
- 2.5.3. Feature Extraction
- 2.5.4. Classification
- 2.5.5. Matching
- 2.5.6. Searching
- 2.5.7. Manual Verification
- 2.6. Criminal Applications
- 2.6.1. National Systems
- 2.6.2. Local Systems
- 2.6.3. Interoperability
- 2.6.4. "Daubert" Questions
- 2.7. Civil Applications
- 2.7.1. Welfare Fraud Reduction
- 2.7.2. Border Control
- 2.7.3. Driver registration
- 2.8. Commercial Applications
- 2.8.1. Miniaturized Sensors
- 2.8.2. Personal Access Protection
- 2.8.3. Banking Security
- 2.8.4. Business-to-Business Transactions
- References
- 3. Iris Recognition
- 3.1. Introduction
- 3.2. Anatomical and Physiological Underpinnings
- 3.3. Sensing
- 3.4. Iris signature representation and matching
- 3.4.1. Localization
- 3.4.2. Representation
- 3.4.3. Matching
- 3.5. Systems and performance
- 3.6. Future directions
- References
- 4. Face Recognition
- 4.1. Introduction
- 4.2. Background
- 4.3. Face Detection
- 4.4. Face Recognition: Representation and Classification
- 4.4.1. Some Representation Techniques and Their Applications to Face Recognition
- 4.4.2. Some Classification Techniques and Their Applications to Face Recognition
- 4.5. Kernel-Based Methods and 3D Model-based Methods for Face Recognition
- 4.6. Learning the Face Space
- 4.6.1. Evolutionary Pursuit
- 4.6.2. Face Recognition Using Evolutionary Pursuit
- 4.7. Conclusion
- References
- 5. Elements of Speaker Verification
- 5.1. Introduction
- 5.1.1. The Speaker Verification Problem
- 5.2. Features and Models
- 5.2.1. Speech Features
- 5.2.2. Speaker Models
- 5.3. Additional Methods for Managing Variability
- 5.3.1. Channel Normalization and Modeling
- 5.3.2. Constraining the Text
- 5.4. Measuring Performance
- 5.4.1. How Well do These Systems Perform?
- 5.5. Alternative Approaches
- 5.5.1. Speech Recognition Approaches
- 5.5.2. Words (and Phonetic Units) Count
- 5.5.3. Models Exploring the Shape of Feature Space
- 5.6. Summary
- References
- 6. Technology Evaluation of Fingerprint Verification Algorithms
- 6.1. Introduction
- 6.2. FVC2000 Organization and Algorithms Submission Rules
- 6.3. Databases
- 6.4. Performance Evaluation
- 6.5. Results
- 6.6. Organization of FVC2002
- 6.7. Conclusions
- Appendix A
- Appendix B
- References
- 7. Methods for Assessing Progress in Face Recognition
- 7.1. Introduction
- 7.2. Face Recognition Evaluations
- 7.2.1. Introduction to FERET and FRVT 2000
- 7.2.2. September 1996 FERET Evaluation Protocol
- 7.2.3. Data Sets
- 7.2.4. FERET and FRVT 2000 Results
- 7.2.5. Conclusions Drawn from the FERET Evaluations and FRVT 2000
- 7.3. Meta-Analysis
- 7.3.1. Introduction to Meta-Analysis
- 7.3.2. Methodology for Selecting Papers
- 7.3.3. Analysis of Performance Scores - Viewing the Data Through Histograms
- 7.3.4. Evaluation of Experiments with a Baseline
- 7.3.5. Meta-Analysis Conclusions
- 7.4. Conclusion
- Acknowledgements
- References
- 8. The NIST speaker recognition evaluation program
- 8.1. Introduction
- 8.2. NIST Speaker Recognition Evaluation Tasks
- 8.2.1. One-Speaker Detection
- 8.2.2. Two-Speaker Detection
- 8.2.3. Speaker Tracking
- 8.2.4. Speaker Segmentation
- 8.3. Data
- 8.3.1. Speaker Training
- 8.3.2. Test Segments
- 8.4. Performance Measure
- 8.5. Evaluation Results
- 8.6. Factors Affecting Detection Performance
- 8.6.1. Duration
- 8.6.2. Pitch
- 8.6.3. Handset Differences
- 8.6.4. Handset Type
- 8.6.5. Landline vs. Cellular
- 8.7. Extended Data Evaluation
- 8.8. Multimodal Evaluation
- 8.9. Future Plans
- References
- 9. Large-Scale Identification System Design
- 9.1. Introduction
- 9.1.1. Historical Background
- 9.1.2. Large-Scale Identification Systems: Requirements and Basic Features
- 9.2. Extrapolation of Accuracy
- 9.2.1. Introduction
- 9.2.2. Key Concepts
- 9.2.3. Method 1: Extrapolation from Experiences
- 9.2.4. Method 2: Identification as a Succession of N Verifications
- 9.2.5. Method 3: Extrapolation with Extreme Value
- 9.2.6. Method 4: Extrapolation when the Distance Can Be Modeled
- 9.2.7. Influence of Classification
- 9.3. Conclusion
- Appendix
- References
- 10. Biometric System Integration
- 10.1. Understanding, Describing and Documenting the Requirements
- 10.2. Choosing the Technology
- 10.3. Application Development
- 10.4. Integration with Existing System Architecture
- 10.5. Templates and Enrollment Management
- 10.6. Understanding User Psychology
- 10.7. Fine Tuning the System
- 10.8. Ongoing Management
- 10.9. Related Issues
- References
- 11. Biometrics and the US Constitution
- 11.1. Introduction
- 11.1.1. Privacy Versus Security; Mankind Versus Machine
- 11.1.2. The Growth of Both Anonymous Public Transactions and the Complexity of Identification
- 11.1.3. Constitutional Concerns
- 11.2. Due Process
- 11.2.1. Entitlements and Rights
- 11.2.2. Instrumental and Intrinsic Approaches
- 11.2.3. Constitutional Development: From the Intrinsic to the Instrumental Approach of Procedural Due Process
- 11.2.4. The Enigma of Substantive Due Process
- 11.3. Individual Privacy
- 11.3.1. The Basis of an Inferred Right to Privacy
- 11.3.2. Privacy and the Fourth Amendment
- 11.3.3. Privacy and the Fifth Amendment
- 11.3.4. Privacy of Personal Information
- 11.4. Conclusions
- References and Notes
- 12. Privacy Issues in the Application of Biometrics: a European Perspective
- 12.1. Introduction
- 12.2. Privacy - from Philosophical Concept to a Human Right
- 12.3. The European Personal Data Directive
- 12.4. Applying the Directive and National Laws to Biometric Systems
- 12.4.1. Biometric Data as "Personal Data"
- 12.4.2. Biometrics and Sensitive Data
- 12.4.3. Proportionality Principle
- 12.4.4. First Principle Compliance - Fair and Lawful Processing
- 12.4.5. Fourth Principle Compliance - Accuracy
- 12.4.6. Seventh Principle Compliance - Security
- 12.4.7. Eighth Principle Compliance - Transfer to Third Countries
- 12.4.8. Automatic Decision-Making
- 12.4.9. Exemptions
- 12.5. Article 8 of the European Human Rights Convention
- 12.6. The Role of Privacy-Enhancing Technologies
- 12.7. Looking to the Future
- 12.8. Social and Psychological Context of the Application of Biometric Methods
- 12.9. Conclusions
- References
- Index
