Adaptive User Agents for Intelligent Biometric Applications

Mavity, Nick and Deravi, Farzin and Fairhurst, Michael (2004) Adaptive User Agents for Intelligent Biometric Applications. In: Applications and Science in Soft Computing. Advances in Soft Computing . Springer, Berlin, Germany, pp. 109-113. ISBN 978-3-540-40856-7. E-ISBN 978-3-540-45240-9. (doi:10.1007/978-3-540-45240-9_44) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:7229)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL: http://dx.doi.org/10.1007/978-3-540-45240-9_44

Abstract

Interest in biometric systems for identity authentication has been growing in recent years. The strengths of biometric systems are well known [2], however, the success of any biometric system is measured ultimately by its usability and user acceptance. Serious obstacles to wider adoption of biometric systems include user interface issues that result in significant failure to enroll and failure to verify rates. Poor templates and template aging are important factors that need to be addressed by any biometric system developer.

Item Type:	Book section
DOI/Identification number:	10.1007/978-3-540-45240-9_44
Subjects:	T Technology > TK Electrical engineering. Electronics. Nuclear engineering > TK7800 Electronics > TK7880 Applications of electronics > TK7882.B56 Biometric identification
Divisions:	Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User:	Yiqing Liang
Date Deposited:	05 Aug 2009 08:37 UTC
Last Modified:	05 Nov 2024 09:39 UTC
Resource URI:	https://kar.kent.ac.uk/id/eprint/7229 (The current URI for this page, for reference purposes)

University of Kent Author Information

Deravi, Farzin.

Creator's ORCID:	https://orcid.org/0000-0003-0885-437X
CReDIT Contributor Roles:

Fairhurst, Michael.

Creator's ORCID:
CReDIT Contributor Roles:

Depositors only (login required):

Altmetric

Download Statistics

Total unique views for this document in KAR since July 2020. For more details click on the image.