Multimodal Biometric Systems

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.

"This book provides an in-depth description of existing and fresh fusion approaches for multimodal biometric systems, covering relevant topics affecting the security and intelligent industries"--Provided by publisher.

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.

Because of the accelerating progress in biometrics research and the latest nation-state threats to security, this book's publication is not only timely but also much needed. This volume contains seventeen peer-reviewed chapters reporting the state of the art in biometrics research: security issues, signature verification, fingerprint identification, wrist vascular biometrics, ear detection, face detection and identification (including a new survey of face recognition), person re-identification, electrocardiogram (ECT) recognition, and several multi-modal systems. This book will be a valuable resource for graduate students, engineers, and researchers interested in understanding and investigating this important field of study.

Details multimodal biometrics and its exceptional utility for increasingly reliable human recognition systems. Reveals the substantial advantages of multimodal systems over conventional identification methods.

This interdisciplinary volume presents a detailed overview of the latest advances and challenges remaining in the field of adaptive biometric systems. A broad range of techniques are provided from an international selection of pre-eminent authorities, collected together under a unified taxonomy and designed to be applicable to any pattern recognition system. Features: presents a thorough introduction to the concept of adaptive biometric systems; reviews systems for adaptive face recognition that perform self-updating of facial models using operational (unlabeled) data; describes a novel semi-supervised training strategy known as fusion-based co-training; examines the characterization and recognition of human gestures in videos; discusses a selection of learning techniques that can be applied to build an adaptive biometric system; investigates procedures for handling temporal variance in facial biometrics due to aging; proposes a score-level fusion scheme for an adaptive multimodal biometric system.

Biometric Systems provides practitioners with an overview of the principles and methods needed to build reliable biometric systems. It covers three main topics: key biometric technologies, design and management issues, and the performance evaluation of biometric systems for personal verification/identification. The four most widely used technologies are focused on - speech, fingerprint, iris and face recognition. Key features include: in-depth coverage of the technical and practical obstacles which are often neglected by application developers and system integrators and which result in shortfalls between expected and actual performance; and protocols and benchmarks which will allow developers to compare performance and track system improvements.

MULTIMODAL BIOMETRIC AND MACHINE LEARNING TECHNOLOGIES With an increasing demand for biometric systems in various industries, this book on multimodal biometric systems, answers the call for increased resources to help researchers, developers, and practitioners. Multimodal biometric and machine learning technologies have revolutionized the field of security and authentication. These technologies utilize multiple sources of information, such as facial recognition, voice recognition, and fingerprint scanning, to verify an individual???s identity. The need for enhanced security and authentication has become increasingly important, and with the rise of digital technologies, cyber-attacks and identity theft have increased exponentially. Traditional authentication methods, such as passwords and PINs, have become less secure as hackers devise new ways to bypass them. In this context, multimodal biometric and machine learning technologies offer a more secure and reliable approach to authentication. This book provides relevant information on multimodal biometric and machine learning technologies and focuses on how humans and computers interact to ever-increasing levels of complexity and simplicity. The book provides content on the theory of multimodal biometric design, evaluation, and user diversity, and explains the underlying causes of the social and organizational problems that are typically devoted to descriptions of rehabilitation methods for specific processes. Furthermore, the book describes new algorithms for modeling accessible to scientists of all varieties. Audience Researchers in computer science and biometrics, developers who are designing and implementing biometric systems, and practitioners who are using biometric systems in their work, such as law enforcement personnel or healthcare professionals.