Multimodal Biometric Systems Security and Applications
Many governments around the world are calling for the use of biometric systems to provide crucial societal functions, consequently making it an urgent area for action. The current performance of some biometric systems in terms of their error rates, robustness, and system security may prove to be inadequate for large-scale applications to process millions of users at a high rate of throughput.
This book focuses on fusion in biometric systems. It discusses the present level, the limitations, and proposed methods to improve performance. It describes the fundamental concepts, current research, and security-related issues. The book will present a computational perspective, identify challenges, and cover new problem-solving strategies, offering solved problems and case studies to help with reader comprehension and deep understanding.
This book is written for researchers, practitioners, both undergraduate and post-graduate students, and those working in various engineering fields such as Systems Engineering, Computer Science, Information Technology, Electronics, and Communications.
Chapter 1.Deep Learning Based Computer Vision: Security, Application & Opportunities.
Chapter 2. Recognition of Foggy Image for Surveillance Application.
Chapter 3. FishNet: Automated Fish Species Recognition Network for Underwater Images.
Chapter 4. Person Identification in UAV Shot Videos by using Machine Learning.
Chapter 5. ECG Based Biometric Authentication Systems using Artificial Intelligence methods.
Chapter 6. False Media Detection by using Deep-Learning.
Chapter 7. Evaluation of Text-Summarization Technique.
Chapter 8. Smart Metro Ticket Management by using Biometric.
Chapter 9. Internet of things: Security Issues, Challenges and its Applications.
Chapter 10. Wireless sensor network for IoT based ECG monitoring system using NRF and LabVIEW.
Chapter 11. Towards Secure Deployment on the Internet of Robotic Things: Architecture, Applications, and Challenges.