Advanced Hand-based Biometrics - Hardcover

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David Zhang (Life Fellow, IEEE) graduated from Peking University, Beijing, China, in 1974, and received the first Ph.D. degree in computer science from Harbin Institute of Technology, Harbin, China, in 1985, and the second Ph.D. degree in electrical and computer engineering from the University of Waterloo, Waterloo, ON, Canada, in 1994. He has been a Chair Professor at The Hong Kong Polytechnic University, Hong Kong, where he was the Founding Director of the Biometrics Research Centre (UGC/CRC), supported by the Hong Kong SAR Government since 1998. He is currently a Distinguished Presidential Chair Professor at The Chinese University of Hong Kong (CUHK-Shenzhen), Shenzhen, China. He has been working on pattern recognition, image processing, and biometrics, creating various famous directions, including medical biometrics and computerized TCM. Prof. Zhang has been selected as a fellow of the Royal Society of Canada (RSC) and the Canadian Academy of Engineering (CAE). He is also a Croucher Senior Research Fellow, a Distinguished Speaker of the IEEE Computer Society, and an IAPR and AAIA Fellow. He has been listed as a Global Highly Cited Researcher in Engineering by Clarivate Analytics for eight years. He is also ranked 70th with H-Index 133 in the Top 1000 Scientists for International Computer Science in 2023. Dandan Fan received the B.S. degree in mechanical design and manufacturing and automation from Southwest Jiaotong University, Cheng Du, in 2013, the M.S. degree in software engineering from Xi’an Jiaotong University, Xi’an, in 2019. She is currently pursuing the Ph.D. degree with School of Data Science, the Chinese University of Hong Kong (Shenzhen), Shenzhen. Her current research interests include biometrics and computer vision. Xu Liang received the B.S. degree in communication engineering from China University of Geosciences, Wu Han, in 2012, the M.S. and Ph.D. degrees in computer science and technology from Harbin Institute of Technology, Shenzhen, China, in 2016 and 2023, respectively. From 2016 to 2017, he was a Research Assistant with the Biometrics Research Centre, Hong Kong Polytechnic University. He is currently an Associate Professor with the School of Software, Northwestern Polytechnical University, Xi'an, China. His research interests include biometrics and computer vision. Bob Zhang (Senior Member, IEEE) received the Ph.D. degree in electrical and computer engineering from the University of Waterloo, Waterloo, ON, Canada, in 2011. After graduating from the University of Waterloo, he remained with the Center for Pattern Recognition and Machine Intelligence, and later he was a Postdoctoral Researcher with the Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA. He is currently an Associate Professor with the Department of Computer and Information Science, University of Macau, Macau. His research interests include biometrics, pattern recognition, and image processing. He is a Technical Committee Member of the IEEE Systems, Man, and Cybernetics Society and Associate Editors of IEEE Transactions on Image Processing, IEEE Transactions on Systems, Man, and Cybernetics: Systems, IEEE Transactions on Neural Networks and Learning Systems, and Artificial Intelligence Review.

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This book offers a scholarly examination of innovative biometric recognition technologies, focusing on palmprint, finger-knuckle-print, palm-vein, dorsal-hand-vein, and multi-modal hand-based recognition systems. It is tailored for an academic and professional audience, including researchers, academics, and industry practitioners engaged in the field of biometrics, pattern recognition, and artificial intelligence.

The book's significance lies in its comprehensive analysis of state-of-the-art hand-based biometric recognition methods. It provides a systematic overview of various traits and recent technological advancements, offering readers insights into the practical applications and theoretical foundations of these emerging biometric modalities. The content encompasses detailed discussions on feature extraction, matching algorithms, and fusion techniques, highlighting their implications for enhancing authentication accuracy and security.

The primary benefits of this book include its thorough coverage of advanced hand-based biometric recognition, its presentation of the latest research findings, and its exploration of cross-disciplinary applications. It is intended to equip readers with an in-depth understanding of the current landscape and future prospects of hand-based biometrics. The book assumes that readers possess a foundational knowledge of pattern recognition and machine learning, which are prerequisites for grasping the presented concepts and methodologies.