This comprehensive guide provides a detailed overview of modern biometrics, which allows a person to be identified and authenticated based on recognizable, unique, and verifiable data. Biometrics technologies include detection of dormant fingerprints, iris, gait, or facial and voice recognition. Today, biometrics powers cutting-edge security algorithms. Biometrics is used for access into banks, airports or personal smartphones, which means that your money and personal information can be stored safely. Each chapter starts with a comprehensive review of the biometrics technology and its algorithmic description, describes how it works, and outlines all of the applicable and modern use cases of that technology. This book will be an invaluable companion guide to students wishing to become system designers, micro-engineers, security algorithms creators, security experts, and electronic security system manufacturers working on controls or microchips.
Author(s): Adele Kuzmiakova
Publisher: Apress
Year: 2022
Language: English
Pages: 248
Cover
Title Page
Copyright
ABOUT THE EDITOR
TABLE OF CONTENTS
List of Figures
List of Tables
List of Abbreviations
Preface
Chapter 1 Machine Learning for Biometrics
1.1. Introduction
1.2. Condition of the Art on Face Biometrics
1.3. Latest Advances in Machine Learning
1.4. Applications
References
Chapter 2 Biometric Detection Recognition Techniques
2.1. Introduction
2.2. Physiological Qualities
2.3. Behavioral Qualities
2.4. Factors of Assessment
2.5. Biometric Identification Framework
2.6. Criteria of Choosing Biometric Feature
2.7. Main Research Challenges in the Biometric Systems
2.8. Development of Biometric Identification
2.9. Discussion and Clarification of Unsolved Issues
References
Chapter 3 Soft Biometrics for Human Recognition
3.1. Introduction
3.2. Soft Biometrics
3.3. Soft Biometrics Current Trends
3.4. Future work and challenges
References
Chapter 4 Eye Recognition Technique and its Characteristics
4.1. Introduction
4.2. Recognition through iris
4.3. Recognition by Retina
4.4. Characteristics of Iris and Retina Recognition Technology
References
Chapter 5 Machine Learning in Biometric Signature Verification
5.1. Introduction
5.2. Background
5.3. Stages of the Signature Verification System
5.4. A Review of Signature Verification Systems
5.5. Trends and Challenges of a Signature Verification System
References
Chapter 6 Fingerprints Classification Using Machine Learning and Image Analysis
6.1. Introduction
6.2. Application of Fingerprint Identification
6.3. Related Work
6.4. Existing Technologies for Fingerprint Analysis
6.5. Proposed Fingerprint Image Pre-processing Method
6.6. Classification Fingerprint Founded on Random Forest and Decision Tree with Singularity Features
References
Chapter 7 Artificial Intelligence in Biometrics
7.1. Introduction
7.2. Historical Background
7.3. Findings
7.4. Summary
References
Chapter 8 Countering the Presentation Attacks in Recognition of Face, Iris, and Fingerprint
8.1. Introduction
8.2. Detection of Face Presentation Attack
8.3. Detection of Fingerprint Presentation Attack
8.4. Detection of Iris Presentation Attack
8.5. Integrated Frameworks for Detecting Presentation Attacks
8.6. Datasets and Metrics
References
Index
Back Cover
