Computer vision is an effective solution in a diverse range of real-life applications. With the advent of the machine and deep learning paradigms, this book adopts machine and deep learning algorithms to leverage digital image processing for designing accurate biometrical applications. In this aspect, it presents the advancements made in computer vision to biometric applications design approach using emerging technologies. It discusses the challenges of designing efficient and accurate biometric-based systems, which is a key issue that can be tackled via computer vision-based techniques.

Key Features

Discusses real-life applications of emerging techniques in computer vision systems
Offers solutions on real-time computer vision and biometrics applications to cater to the needs of current industry
Presents case studies to offer ideas for developing new biometrics-based products
Offers problem-based solutions in the field computer vision and real-time biometric applications for secured human authentication
Works as a ready resource for professionals and scholars working on emerging topics of computer vision for biometrics

The book is for academic researchers, scholars and students in Computer Science, Information Technology, Electronics and Electrical Engineering, Mechanical Engineering, management, academicians, researchers, scientists and industry people working on computer vision and biometrics applications.

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Yes, you can access Leveraging Computer Vision to Biometric Applications by Arvind Selwal,Deepika Sharma,Mukesh Mann,Sudeshna Chakraborty,Valentina E. Balas,Ouh Eng Lieh in PDF and/or ePUB format, as well as other popular books in Computer Science & Computer Engineering. We have over one million books available in our catalogue for you to explore.

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Index

Cover Page
Half-Title Page
Series Page
Title Page
Copyright Page
Contents
Preface
Editors
List of Contributors
Chapter 1 Biometrics: Introduction and Applications
Chapter 2 Security and Privacy Issues in Existing Biometric Systems and Solutions
Chapter 3 Examining the Vulnerabilities of Biometric Systems: Privacy and Security Perspectives
Chapter 4 Biometric Systems Security and Privacy Issues
Chapter 5 Enhancing Computer Vision Enabled Biometric Applications: Current Trend, Challenges and Future Opportunities
Chapter 6 MFDLD: Multiscale Fused Discriminant Local Descriptor for Face Recognition
Chapter 7 The Facial Façade: Development, Relevance, and Examination of Facial Imagery in Forensic Science
Chapter 8 A Hybrid Deep Feature Selection Framework for Speaker Accent Recognition
Chapter 9 Secure Transaction in Animal Biometric Assessment
Chapter 10 Novel Efficient Approach that Enhances Security over Biometric Systems Using Computer Vision Techniques
Chapter 11 Enhancing Face Anti-Spoofing with Three-Stream CNNs: Leveraging Color Space Analysis
Chapter 12 Computer-Vision Techniques for Video Analysis
Chapter 13 An Efficient and Robust Iris Spoof Detection Pipeline via Optimized Deep Features
Chapter 14 Advancements in Computer Vision for Biometrics Enhancing Security and Identification
Chapter 15 Digital Forensics and Its Applications
Chapter 16 Fingerprint Security and the Internet of Things (IoT) in the Digital Era
Index

About this book

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Table of contents