In today's security-conscious society, real-world applications for authentication or identification require a highly accurate system for recognizing individual humans. The required level of performance cannot be achieved through the use of a single biometric such as face, fingerprint, ear, iris, palm, gait or speech. Fusing multiple biometrics enables the indexing of large databases, more robust performance and enhanced coverage of populations. Multiple biometrics are also naturally more robust against attacks than single biometrics. This book addresses a broad spectrum of research issues on multibiometrics for human identification, ranging from sensing modes and modalities to fusion of biometric samples and combination of algorithms. It covers publicly available multibiometrics databases, theoretical and empirical studies on sensor fusion techniques in the context of biometrics authentication, identification and performance evaluation and prediction.
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Dr Bir Bhanu is the Distinguished Professor of Electrical Engineering and serves as the Director of the Interdisciplinary Center for Research in Intelligent Systems and the Visualization and Intelligent Systems Laboratory at the University of California, Riverside (UCR). He is a coauthor of seven authored books and three edited books, has 12 patents, and has authored more than 350 reviewed technical publications, including more than 100 journal papers.
Dr Venu Govindaraju is a UB Distinguished Professor of Computer Science and Engineering at the University at Buffalo (SUNY Buffalo) and the founder of the Center for Unified Biometrics and Sensors (CUBS). He has coauthored more than 300 reviewed technical papers, four U.S. patents and two books.
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Hardcover. Condition: new. Hardcover. In today's security-conscious society, real-world applications for authentication or identification require a highly accurate system for recognizing individual humans. The required level of performance cannot be achieved through the use of a single biometric such as face, fingerprint, ear, iris, palm, gait or speech. Fusing multiple biometrics enables the indexing of large databases, more robust performance and enhanced coverage of populations. Multiple biometrics are also naturally more robust against attacks than single biometrics. This book addresses a broad spectrum of research issues on multibiometrics for human identification, ranging from sensing modes and modalities to fusion of biometric samples and combination of algorithms. It covers publicly available multibiometrics databases, theoretical and empirical studies on sensor fusion techniques in the context of biometrics authentication, identification and performance evaluation and prediction. This book addresses research issues regarding multibiometrics for human identification, examining their advantages and evaluation. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780521115964