Handbook Of Multibiometrics

Description

Consistent advances in biometrics help to address problems that plague traditional human recognition methods and offer significant promise for applications in security as well as general convenience. In particular, newly evolving systems can measure multiple physiological or behavioral traits and thereby increase overall reliability that much more.

Multimodal Biometrics provides an accessible, focused examination of the science and technology behind multimodal human recognition systems, as well as their ramifications for security systems and other areas of application. After clearly introducing multibiometric systems, the book demonstrates the noteworthy advantages of these systems over their traditional and unimodal counterparts. In addition, the work describes the various scenarios possible when consolidating evidence from multiple biometric systems and examines multimodal system design and methods for computing user-specific parameters.

Topics and features:

* Introduces readers to the rapidly evolving field of multimodal biometrics and its exceptional utility for increasingly reliable human recognition systems

* Reveals the substantial advantages of multimodal systems over conventional identification methods

* Shows how multimodal approaches address the problems of universality and spoofing

* Describes techniques to perform fusion, especially at the matching score level

* Examines existing multimodal databases and what they have to offer

* Uses numerous examples and illustrations to support the explanations

This authoritative, comprehensive volume on multimodal biometric systems concisely and clearly outlines their great promise for higher reliability than conventional human verification systems. It is an essential resource for researchers, professionals, and students who will need to know and use the concepts, principles, and methods of advanced biometrics.

Introduction.- Architecture and levels of fusion.- Techniques to perform classifier fusion.- Single biometric multiple features.- Single biometric multiple matchers.- Single biometric multiple units.- Multimodal biometrics.- Learning user-specific parameters.- Multimodal biometric databases.- Integrating COTS systems.- Performance evaluation of multimodal systems.- Bibliography.- Index.