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Cross disciplinary biometric systems help boost the performance of the conventional systems. Not only is the recognition accuracy significantly improved, but also the robustness of the systems is greatly enhanced in the challenging environments, such as varying illumination conditions. By leveraging the cross disciplinary technologies, face recognition systems, fingerprint recognition systems, iris recognition systems, as well as image search systems all benefit in terms of recognition performance. Take face recognition for an example, which is not only the most natural way human beings recognize the identity of each other, but also the least privacy-intrusive means because people show their face publicly every day. Face recognition systems display superb performance when they capitalize on the innovative ideas across color science, mathematics, and computer science (e.g., pattern recognition, machine learning, and image processing). The novel ideas lead to the development of new color models and effective color features in color science; innovative features from wavelets and statistics, and new kernel methods and novel kernel models in mathematics; new discriminant analysis frameworks, novel similarity measures, and new image analysis methods, such as fusing multiple image features from frequency domain, spatial domain, and color domain in computer science; as well as system design, new strategies for system integration, and different fusion strategies, such as the feature level fusion, decision level fusion, and new fusion strategies with novel similarity measures.
Cross disciplinary biometric systems help boost the performance of the conventional systems. Not only is the recognition accuracy significantly improved, but also the robustness of the systems is greatly enhanced in the challenging environments, such as varying illumination conditions. By leveraging the cross disciplinary technologies, face recognition systems, fingerprint recognition systems, iris recognition systems, as well as image search systems all benefit in terms of recognition performance. Take face recognition for an example, which is not only the most natural way human beings recognize the identity of each other, but also the least privacy-intrusive means because people show their face publicly every day. Face recognition systems display superb performance when they capitalize on the innovative ideas across color science, mathematics, and computer science (e.g., pattern recognition, machine learning, and image processing). The novel ideas lead to the development of new color models and effective color features in color science; innovative features from wavelets and statistics, and new kernel methods and novel kernel models in mathematics; new discriminant analysis frameworks, novel similarity measures, and new image analysis methods, such as fusing multiple image features from frequency domain, spatial domain, and color domain in computer science; as well as system design, new strategies for system integration, and different fusion strategies, such as the feature level fusion, decision level fusion, and new fusion strategies with novel similarity measures.
Privacy and Technologies of Identity: A Cross-Disciplinary Conversation provides an overview of ways in which technological changes raise privacy concerns. It then addresses four major areas of technology: RFID and location tracking technology; biometric technology, data mining; and issues with anonymity and authentication of identity. Many of the chapters are written with the non-specialist in mind, seeking to educate a diverse audience on the "basics" of the technology and the law and to point out the promise and perils of each technology for privacy. The material in this book provides an interface between legal and policy approaches to privacy and technologies that either threaten or enhance privacy. This book grew out of the Fall 2004 CIPLIT(r) Symposium on Privacy and Identity: The Promise and Perils of a Technological Age, co-sponsored by DePaul University's College of Law and School of Computer Science, Telecommunications and Information Systems. The Symposium brought together leading researchers in advanced technology and leading thinkers from the law and policy arenas, many of whom have contributed chapters to the book. Like the Symposium, the book seeks to contribute to a conversation among technologists, lawyers, and policymakers about how best to handle the challenges to privacy that arise from recent technological advances.
The need for intelligent machines in areas such as medical diagnostics, biometric security systems, and image processing motivates researchers to develop and explore new techniques, algorithms, and applications in this evolving field.Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition: Advancing Technologies provides a common platform for researchers to present theoretical and applied research findings for enhancing and developing intelligent systems. Through its discussions of advances in and applications of pattern recognition technologies and artificial intelligence, this reference highlights core concepts in biometric imagery, feature recognition, and other related fields, along with their applicability.
Biometrics and Kansei Engineering is the first book to bring together the principles and applications of each discipline. The future of biometrics is in need of new technologies that can depend on people’s emotions and the prediction of their intention to take an action. Behavioral biometrics studies the way people walk, talk, and express their emotions, and Kansei Engineering focuses on interactions between users, products/services and product psychology. They are becoming quite complementary. This book also introduces biometric applications in our environment, which further illustrates the close relationship between Biometrics and Kansei Engineering. Examples and case studies are provided throughout this book. Biometrics and Kansei Engineering is designed as a reference book for professionals working in these related fields. Advanced-level students and researchers studying computer science and engineering will find this book useful as a reference or secondary text book as well.
"This book provides a common platform for researchers to present theoretical and applied research findings for enhancing and developing intelligent systems, discussing advances in and applications of pattern recognition technologies and artificial intelligence"--
Biometric recognition, or simply biometrics, is the science of establishing the identity of a person based on physical or behavioral attributes. It is a rapidly evolving field with applications ranging from securely accessing one’s computer to gaining entry into a country. While the deployment of large-scale biometric systems in both commercial and government applications has increased the public awareness of this technology, "Introduction to Biometrics" is the first textbook to introduce the fundamentals of Biometrics to undergraduate/graduate students. The three commonly used modalities in the biometrics field, namely, fingerprint, face, and iris are covered in detail in this book. Few other modalities like hand geometry, ear, and gait are also discussed briefly along with advanced topics such as multibiometric systems and security of biometric systems. Exercises for each chapter will be available on the book website to help students gain a better understanding of the topics and obtain practical experience in designing computer programs for biometric applications. These can be found at: http://www.csee.wvu.edu/~ross/BiometricsTextBook/. Designed for undergraduate and graduate students in computer science and electrical engineering, "Introduction to Biometrics" is also suitable for researchers and biometric and computer security professionals.
Privacy and Technologies of Identity: A Cross-Disciplinary Conversation provides an overview of ways in which technological changes raise privacy concerns. It then addresses four major areas of technology: RFID and location tracking technology; biometric technology, data mining; and issues with anonymity and authentication of identity. Many of the chapters are written with the non-specialist in mind, seeking to educate a diverse audience on the "basics" of the technology and the law and to point out the promise and perils of each technology for privacy. The material in this book provides an interface between legal and policy approaches to privacy and technologies that either threaten or enhance privacy. This book grew out of the Fall 2004 CIPLIT(r) Symposium on Privacy and Identity: The Promise and Perils of a Technological Age, co-sponsored by DePaul University's College of Law and School of Computer Science, Telecommunications and Information Systems. The Symposium brought together leading researchers in advanced technology and leading thinkers from the law and policy arenas, many of whom have contributed chapters to the book. Like the Symposium, the book seeks to contribute to a conversation among technologists, lawyers, and policymakers about how best to handle the challenges to privacy that arise from recent technological advances.
"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.