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Multimodal Biometrics and Intelligent Image Processing for Security Systems

Book Description

Although it is a relatively new approach to biometric knowledge representation, multimodal biometric systems have emerged as an innovative alternative that aids in developing a more reliable and efficient security system. Multimodal Biometrics and Intelligent Image Processing for Security Systems provides an in-depth description of existing and fresh fusion approaches for multimodal biometric systems. Covering relevant topics affecting the security and intelligent industries, this reference will be useful for readers from both academia and industry in the areas of pattern recognition, security, and image processing domains.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Dedication
  5. Foreword
  6. Preface
  7. Acknowledgment
  8. Section 1: Biometric Overview and Trends
    1. Chapter 1: Introduction
      1. ABSTRACT
      2. 1. A HISTORICAL LOOK AT ARTIFICIAL INTELLIGENCE
      3. 2. EVOLUTIONAL COMPUTING AND NEURAL NETWORKS
      4. 3. COMPUTATIONAL INTELLIGENCE AND BIOMETRICS
      5. 4. SUMMARY
    2. Chapter 2: Overview of Biometrics and Biometrics Systems
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. BIOMETRIC IDENTIFIERS
      4. 3. ATTRIBUTES OF BIOMETRIC IDENTIFIERS
      5. 4. COMPONENTS OF BIOMETRIC SYSTEM
      6. 5. BIOMETRIC VERIFICATION
      7. 6. BIOMETRIC IDENTIFICATION
      8. 7. BIOMETRIC SYSTEM PERFORMANCE
      9. 8. APPLICATIONS OF BIOMETRIC SYSTEM
      10. 9. LIMITATIONS OF BIOMETRIC SYSTEM
      11. 10. SUMMARY
    3. Chapter 3: Biometric Image Processing
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. APPEARANCE-BASED IMAGE PROCESSING IN BIOMETRICS
      4. 3. TOPOLOGY-BASED INTELLIGENT PATTERN ANALYSIS IN BIOMETRICS
      5. 4. MODEL-BASED BEHAVIORAL BIOMETRICS
      6. 5. SUMMARY
  9. Section 2: Current Practices in Information Fusion for Multimodal Biometrics
    1. Chapter 4: Multimodal Biometric System and Information Fusion
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. ADVANTAGES OF MULTIMODAL BIOMETRIC SYSTEM
      4. 3. DEVELOPMENTAL ISSUES OF MULTIBIOMETRIC SYSTEMS
      5. 4. INFORMATION SOURCES FOR MULTIBIOMETRIC SYSTEMS
      6. 5. INFORMATION FUSION
      7. 6. BIOMETRIC INFORMATION FUSION
      8. 7. FUSION BEFORE MATCHING AND FUSION AFTER MATCHING
      9. 8. SUMMARY
    2. Chapter 5: Rank Level Fusion
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. REVIEW OF EXISTING METHODS
      4. 3. PLURALITY VOTING RANK FUSION METHOD
      5. 4. HIGHEST RANK METHOD FOR RANK FUSION
      6. 5. BORDA COUNT RANK FUSION METHOD
      7. 6. LOGISTIC REGRESSION RANK FUSION METHOD
      8. 7. QUALITY-BASED RANK FUSION METHOD
      9. 8. SUMMARY
    3. Chapter 6: Markov Chain for Multimodal Biometric Rank Fusion
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. MARKOV CHAIN
      4. 3. RESEARCH ON MARKOV CHAIN
      5. 4. MARKOV CHAIN FOR MULTIMODAL BIOMETRIC FUSION
      6. 5. SAMPLE RESULTS OBTAINED THROUGH EXPERIMENTATIONS
      7. 6. SUMMARY
    4. Chapter 7: Fuzzy Fusion for Multimodal Biometric
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. FUZZY LOGIC BASICS
      4. 3. RESEARCH ON FUZZY LOGIC-BASED FUSION
      5. 4. FUZZY FUSION OF BIOMETRIC INFORMATION
      6. 5. EXPERIMENT RESULTS FOR FUZZY FUSION OF BIOMETRIC INFORMATION
      7. 6. SUMMARY
  10. Section 3: Applications in Security Systems
    1. Chapter 8: Robotics and Multimodal Biometrics
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. LITERATURE REVIEW
      4. 3. SURVEY OF NON-BIOLOGICAL ENTITIES
      5. 4. AVATAR AUTHENTICATION
      6. 5. APPLICATIONS
      7. 6. SUMMARY AND FUTURE WORK
    2. Chapter 9: Chaotic Neural Networks and Multi-Modal Biometrics
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. SYSTEM ARCHITECTURE
      4. 3. NEURAL NETWORKS METHODOLOGY
      5. 4. CHAOS IN NEURAL NETWORKS
      6. 5. FEATURE SPACE AND DIMENSIONALITY REDUCTION
      7. 6. NEURAL-NETWORKS IN MULTI-MODAL BIOMETRICS
      8. 7. SUBSPACE ANALYSIS AND ASSOCIATE MEMORY
      9. 8. PERFORMANCE OF NEURAL NETWORK ON FINGERPRINT MATCHING
      10. 9. CNN-BASED MINUTIAE MATCHING METHOD
      11. 10. SUMMARY
    3. Chapter 10: Novel Applications of Multimodal Biometrics
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. GAIT ANALYSIS IN MULTI-BIOMETRIC RESEARCH
      4. 3. LITERATURE SURVEY
      5. 4. DETAILED METHODOLOGY
      6. 5. SOCIAL NETWORKS FOR MULTIBIOMETRIC RESEARCH
      7. 6. FUSING SOCIAL CONTEXT WITH GAIT RECOGNITION
      8. 7. IMPLEMENTATION DETAILS AND RESULTS
      9. 8. SUMMARY
    4. Chapter 11: Conclusion
      1. ABSTRACT
      2. 1. BOOK SUMMARY
      3. 2. CONCLUSION
      4. 3. FUTURE RESEARCH DIRECTIONS
  11. Compilation of References
  12. About the Authors
  13. Quotes and Testimonials
    1. QUOTES
    2. TESTIMONIALS
  14. List of Figures
  15. List of Abbreviations
  16. Related References
  17. List of Tables