Biometric System And Data Analysis

This book brings together aspects of statistics and machine learning to provide a comprehensive guide to evaluating, interpreting and understanding biometric data. It naturally leads to topics including data mining and prediction to be examined in detail. The book places an emphasis on the various performance measures available for biometric systems, what they mean, and when they should and should not be applied. The evaluation techniques are presented rigorously, however they are always accompanied by intuitive explanations. This is important for the increased acceptance of biometrics among non-technical decision makers, and ultimately the general public.

This volume helps to fill the gap between data analytics, image processing, and soft computing practices. Soft computing methods are used to focus on data analytics and image processing to develop good intelligent systems. To this end, readers of this volume will find quality research that presents the current trends, advanced methods, and hybridized techniques relating to data analytics and intelligent systems. The book also features case studies related to medical diagnosis with the use of image processing and soft computing algorithms in particular models. Providing extensive coverage of biometric systems, soft computing, image processing, artificial intelligence, and data analytics, the chapter authors discuss the latest research issues, present solutions to research problems, and look at comparative analysis with earlier results. Topics include some of the most important challenges and discoveries in intelligent systems today, such as computer vision concepts and image identification, data analysis and computational paradigms, deep learning techniques, face and speaker recognition systems, and more.

This book discusses all critical privacy and data protection aspects of biometric systems from a legal perspective. It contains a systematic and complete analysis of the many issues raised by these systems based on examples worldwide and provides several recommendations for a transnational regulatory framework. An appropriate legal framework is in most countries not yet in place. Biometric systems use facial images, fingerprints, iris and/or voice in an automated way to identify or to verify (identity) claims of persons. The treatise which has an interdisciplinary approach starts with explaining the functioning of biometric systems in general terms for non-specialists. It continues with a description of the legal nature of biometric data and makes a comparison with DNA and biological material and the regulation thereof. After describing the risks, the work further reviews the opinions of data protection authorities in relation to biometric systems and current and future (EU) law. A detailed legal comparative analysis is made of the situation in Belgium, France and the Netherlands. The author concludes with an evaluation of the proportionality principle and the application of data protection law to biometric data processing operations, mainly in the private sector. Pleading for more safeguards in legislation, the author makes several suggestions for a regulatory framework aiming at reducing the risks of biometric systems. They include limitations to the collection and storage of biometric data as well as technical measures, which could influence the proportionality of the processing. The text is supported by several figures and tables providing a summary of particular points of the discussion. The book also uses the 2012 biometric vocabulary adopted by ISO and contains an extensive bibliography and literature sources.

Biometric recognition-the automated recognition of individuals based on their behavioral and biological characteristic-is promoted as a way to help identify terrorists, provide better control of access to physical facilities and financial accounts, and increase the efficiency of access to services and their utilization. Biometric recognition has been applied to identification of criminals, patient tracking in medical informatics, and the personalization of social services, among other things. In spite of substantial effort, however, there remain unresolved questions about the effectiveness and management of systems for biometric recognition, as well as the appropriateness and societal impact of their use. Moreover, the general public has been exposed to biometrics largely as high-technology gadgets in spy thrillers or as fear-instilling instruments of state or corporate surveillance in speculative fiction. Now, as biometric technologies appear poised for broader use, increased concerns about national security and the tracking of individuals as they cross borders have caused passports, visas, and border-crossing records to be linked to biometric data. A focus on fighting insurgencies and terrorism has led to the military deployment of biometric tools to enable recognition of individuals as friend or foe. Commercially, finger-imaging sensors, whose cost and physical size have been reduced, now appear on many laptop personal computers, handheld devices, mobile phones, and other consumer devices. Biometric Recognition: Challenges and Opportunities addresses the issues surrounding broader implementation of this technology, making two main points: first, biometric recognition systems are incredibly complex, and need to be addressed as such. Second, biometric recognition is an inherently probabilistic endeavor. Consequently, even when the technology and the system in which it is embedded are behaving as designed, there is inevitable uncertainty and risk of error. This book elaborates on these themes in detail to provide policy makers, developers, and researchers a comprehensive assessment of biometric recognition that examines current capabilities, future possibilities, and the role of government in technology and system development.

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.

This book showcases new and innovative approaches to biometric data capture and analysis, focusing especially on those that are characterized by non-intrusiveness, reliable prediction algorithms, and high user acceptance. It comprises the peer-reviewed papers from the international workshop on the subject that was held in Ancona, Italy, in October 2014 and featured sessions on ICT for health care, biometric data in automotive and home applications, embedded systems for biometric data analysis, biometric data analysis: EMG and ECG, and ICT for gait analysis. The background to the book is the challenge posed by the prevention and treatment of common, widespread chronic diseases in modern, aging societies. Capture of biometric data is a cornerstone for any analysis and treatment strategy. The latest advances in sensor technology allow accurate data measurement in a non-intrusive way, and in many cases it is necessary to provide online monitoring and real-time data capturing to support a patient’s prevention plans or to allow medical professionals to access the patient’s current status. This book will be of value to all with an interest in this expanding field.

Biometrics in a Data Driven World: Trends, Technologies, and Challenges aims to inform readers about the modern applications of biometrics in the context of a data-driven society, to familiarize them with the rich history of biometrics, and to provide them with a glimpse into the future of biometrics. The first section of the book discusses the fundamentals of biometrics and provides an overview of common biometric modalities, namely face, fingerprints, iris, and voice. It also discusses the history of the field, and provides an overview of emerging trends and opportunities. The second section of the book introduces readers to a wide range of biometric applications. The next part of the book is dedicated to the discussion of case studies of biometric modalities currently used on mobile applications. As smartphones and tablet computers are rapidly becoming the dominant consumer computer platforms, biometrics-based authentication is emerging as an integral part of protecting mobile devices against unauthorized access, while enabling new and highly popular applications, such as secure online payment authorization. The book concludes with a discussion of future trends and opportunities in the field of biometrics, which will pave the way for advancing research in the area of biometrics, and for the deployment of biometric technologies in real-world applications. The book is designed for individuals interested in exploring the contemporary applications of biometrics, from students to researchers and practitioners working in this field. Both undergraduate and graduate students enrolled in college-level security courses will also find this book to be an especially useful companion.

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.