First book to focus on aspects common to all biometric recognition systems, including input data (biometrics images, and person metadata) plus output (scores) of these systems which leads to a focus on user and group level performance
Case studies and examples from several major biometric modalities included
First book to focus on aspects common to all biometric recognition systems, including input data (biometrics images, and person metadata) plus output (scores) of these systems which leads to a focus on user and group level performance
Case studies and examples from several major biometric modalities included
This book brings together aspects of statistics and machine learning to provide a comprehensive guide to evaluating, interpreting and understanding biometric data. This professional book naturally leads to topics including data mining and prediction, which have been widely applied to other fields but not rigorously to biometrics, 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 that can be used to convey the essence of the statistical concepts to a general audience. This last point is an important one for the increased acceptance of biometrics among non-technical decision makers, and ultimately the general public.
An Overview of Biometrics.- An Introduction to Biometric Data Analysis.- Biometric Matching Basics.- Biometric Data.- Multimodal Systems.- Performance Testing and Reporting.- Definitions.- The Biometric Performance Hierarchy.- System Evaluation: The Statistical Basis of Biometric Systems.- Individual Evaluation: The Biometric Menagerie.- Group Evaluation: Data Mining for Biometrics.- Special Topics in Biometric Data Analysis.- Proof of Identity.- Covert Surveillance Systems.- Vulnerabilities.
Biometric System and Data Analysis: Design, Evaluation, and Data Mining brings together aspects of statistics and machine learning to provide a comprehensive guide to evaluate, interpret and understand biometric data. This professional book naturally leads to topics including data mining and prediction, widely applied to other fields but not rigorously to biometrics.
This volume 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 are always accompanied by intuitive explanations that convey the essence of the statistical concepts in a general manner.
Designed for a professional audience composed of practitioners and researchers in industry, Biometric System and Data Analysis: Design, Evaluation, and Data Mining is also suitable as a reference for advanced-level students in computer science and engineering.
From the reviews:"This book brings together a discussion on biometric systems, statistics, and machine learning. Its aim is to help us understand biometric data, measurements of such systems, and the ability to interpret them is highly desirable. ... The book suits the needs of many practitioners, those involved with data in all its forms, and also would make useful reading for those who are studying systems, cybernetics, and management in the many and varied courses now being made available worldwide.” (W. R. Howard, Kybernetes, Vol. 38 (9), 2009)
Biometric System and Data Analysis: Design, Evaluation, and Data Mining brings together aspects of statistics and machine learning to provide a comprehensive guide to evaluate, interpret and understand biometric data. This professional book naturally leads to topics including data mining and prediction--widely applied to other fields but not rigorously to biometrics--to be examined in detail.
This volume 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 are always accompanied by intuitive explanations that convey the essence of the statistical concepts to a general audience.
Designed for a professional audience composed of practitioners and researchers in industry, Biometric System and Data Analysis: Design, Evaluation, and Data Mining is also suitable as a reference for advanced-level students in computer science and engineering.
From the reviews: "This book brings together a discussion on biometric systems, statistics, and machine learning. Its aim is to help us understand biometric data, measurements of such systems, and the ability to interpret them is highly desirable. ... The book suits the needs of many practitioners, those involved with data in all its forms, and also would make useful reading for those who are studying systems, cybernetics, and management in the many and varied courses now being made available worldwide." (W. R. Howard, Kybernetes, Vol. 38 (9), 2009)
Inhaltsverzeichnis
An Overview of Biometrics.- An Introduction to Biometric Data Analysis.- Biometric Matching Basics.- Biometric Data.- Multimodal Systems.- Performance Testing and Reporting.- Definitions.- The Biometric Performance Hierarchy.- System Evaluation: The Statistical Basis of Biometric Systems.- Individual Evaluation: The Biometric Menagerie.- Group Evaluation: Data Mining for Biometrics.- Special Topics in Biometric Data Analysis.- Proof of Identity.- Covert Surveillance Systems.- Vulnerabilities.
Klappentext
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 book brings together aspects of statistics and machine learning to provide a comprehensive guide to evaluating, interpreting and understanding biometric data. This professional book naturally leads to topics including data mining and prediction, which have been widely applied to other fields but not rigorously to biometrics, 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 that can be used to convey the essence of the statistical concepts to a general audience. This last point is an important one for the increased acceptance of biometrics among non-technical decision makers, and ultimately the general public.
