Research Article
An Adaptive Fusion Framework for Fault-Tolerant Multibiometrics
@INPROCEEDINGS{10.1007/978-3-642-11530-1_17, author={S. Chindaro and Z. Zhou and M. Ng and F. Deravi}, title={An Adaptive Fusion Framework for Fault-Tolerant Multibiometrics}, proceedings={Information Security and Digital Forensics. First International Conference, ISDF 2009, London, United Kingdom, September 7-9, 2009, Revised Selected Papers}, proceedings_a={ISDF}, year={2012}, month={5}, keywords={Adaptive Fusion Multibiometrics Face Recognitions}, doi={10.1007/978-3-642-11530-1_17} }- S. Chindaro
Z. Zhou
M. Ng
F. Deravi
Year: 2012
An Adaptive Fusion Framework for Fault-Tolerant Multibiometrics
ISDF
Springer
DOI: 10.1007/978-3-642-11530-1_17
Abstract
The use of multiple biometrics will work with greater efficiency if all the systems are capable of acquiring biometrics of adequate quality and processing them successfully. However if one or more of the biometrics fails, then the system has to rely on fewer or one biometric. If the individual biometrics are set to use low thresholds, the system maybe vulnerable to falsely accepting impostors. The motivation behind the proposed method is to provide an adaptive fusion platform where the software system can identify failures in certain algorithms and if necessary adapt the current rule to ignore these algorithms and adjust operating points accordingly. Results from experiments carried out on a multi-algorithmic and multi-biometric 3D and 2D database are presented to show that adopting such a system will result in an improvement in efficiency and verification rate.
