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2006 | Buch

Handbook of Multibiometrics

verfasst von: Arun A. Ross, Anil K. Jain, Karthik Nandakumar

Verlag: Springer US

Buchreihe : International Series on Biometrics

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Über dieses Buch

Reliable human authentication schemes are of paramount importance in our highly networked society. Advances in biometrics help address the myriad of problems associated with traditional human recognition methods. The performance and benefits of a biometric system can be significantly enhanced by consolidating the evidence presented by multiple biometric sources. Multibiometric systems are expected to meet the stringent performance requirements imposed by large-scale authentication systems.

Handbook of Multibiometrics, a professional book, introduces multibiometric systems, and demonstrates the noteworthy advantages of these systems over their unimodal counterparts. In addition, this book describes in detail the various scenarios possible when fusing biometric evidence from multiple information sources.

This comprehensive volume on multibiometric systems, concisely and clearly outlines the different fusion methodologies that have been proposed by researchers to integrate multiple biometric traits.

Inhaltsverzeichnis

Frontmatter
Chapter 1. Biometrics: When Identity Matters
Chapter 2. Information Fusion in Biometrics
Chapter 3. Levels of Fusion in Biometrics
Chapter 4. Score Level Fusion
Chapter 5. Fusion Incorporating Ancillary Information
5.4 Summary
In addition to the match scores provided by the biometric matchers, ancillary information may also be available to a multibiometric system depending on the application scenario. Biometric signal quality and soft biometric information are two examples of such additional information that can be utilized to improve the accuracy of a multibiometric system. While biometric signal quality does not explicitly contain any information about the identity of the user, different biometric matchers exhibit different levels of sensitivity to the quality of the acquired biometric sample. This phenomenon can be exploited in a multibiometric system where the match scores or the identity decisions of the matchers can be appropriately weighted during fusion based on the quality of the input biometric sample. Soft biometric characteristics like gender, ethnicity, height and weight directly provide information about the identity of the user. Although the soft biometric information alone is not sufficient for accurate person recognition, they can be used to complement the information provided by the primary biometric identifiers like fingerprint, iris and face. Techniques for automatically extracting soft biometric information and estimating biometric signal quality have been incorporated into biometric systems only recently. Hence, fusion schemes that incorporate such ancillary information have not been thoroughly explored and there is plenty of scope for conducting more in-depth research in this area.
Backmatter
Metadaten
Titel
Handbook of Multibiometrics
verfasst von
Arun A. Ross
Anil K. Jain
Karthik Nandakumar
Copyright-Jahr
2006
Verlag
Springer US
Electronic ISBN
978-0-387-33123-2
Print ISBN
978-0-387-22296-7
DOI
https://doi.org/10.1007/0-387-33123-9

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