An Adaptive Fusion Framework for Fault-Tolerant Multibiometrics

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.