The Handbook of Multibiometrics is a comprehensive guide to the field of multibiometric systems, covering the principles, techniques, and applications of biometric authentication. It is part of the International Series on Biometrics, edited by David D. Zhang and Anil K. Jain. The book provides an in-depth exploration of biometric technologies, including fingerprint, face, voice, iris, and gait recognition, and discusses how they can be combined to improve system accuracy and reliability. It addresses the challenges and limitations of single biometric systems and presents various fusion strategies at different levels, such as sensor, feature, rank, and decision levels. The book also covers the integration of ancillary information, such as soft biometrics (e.g., gender, height, eye color), to enhance authentication performance. It includes detailed discussions on score-level fusion techniques, including density-based, transformation-based, and classifier-based methods, and explores the impact of user-specific parameters on system performance. The book is structured into chapters that introduce the fundamentals of biometrics, discuss various fusion approaches, and present case studies and examples from the literature. It also includes appendices with information on biometric databases and evaluation methods. The authors emphasize the importance of multibiometric systems in large-scale applications, such as border security and secure access control, and highlight the advantages of these systems in terms of accuracy, robustness, and user convenience. The book is intended for researchers, engineers, students, and professionals in the field of biometrics and information fusion.The Handbook of Multibiometrics is a comprehensive guide to the field of multibiometric systems, covering the principles, techniques, and applications of biometric authentication. It is part of the International Series on Biometrics, edited by David D. Zhang and Anil K. Jain. The book provides an in-depth exploration of biometric technologies, including fingerprint, face, voice, iris, and gait recognition, and discusses how they can be combined to improve system accuracy and reliability. It addresses the challenges and limitations of single biometric systems and presents various fusion strategies at different levels, such as sensor, feature, rank, and decision levels. The book also covers the integration of ancillary information, such as soft biometrics (e.g., gender, height, eye color), to enhance authentication performance. It includes detailed discussions on score-level fusion techniques, including density-based, transformation-based, and classifier-based methods, and explores the impact of user-specific parameters on system performance. The book is structured into chapters that introduce the fundamentals of biometrics, discuss various fusion approaches, and present case studies and examples from the literature. It also includes appendices with information on biometric databases and evaluation methods. The authors emphasize the importance of multibiometric systems in large-scale applications, such as border security and secure access control, and highlight the advantages of these systems in terms of accuracy, robustness, and user convenience. The book is intended for researchers, engineers, students, and professionals in the field of biometrics and information fusion.