Multibiometric: Feature Level Fusion Using FKP Multi-Instance biometric
This is an incremental improvement for biometric security systems using finger knuckle prints.
The paper tackled FKP verification by proposing multi-instance feature level fusion with log-Gabor filters, achieving higher performance than single-instance methods on a database of 7,920 images.
This paper proposed the use of multi-instance feature level fusion as a means to improve the performance of Finger Knuckle Print (FKP) verification. A log-Gabor filter has been used to extract the image local orientation information, and represent the FKP features. Experiments are performed using the FKP database, which consists of 7,920 images. Results indicate that the multi-instance verification approach outperforms higher performance than using any single instance. The influence on biometric performance using feature level fusion under different fusion rules have been demonstrated in this paper.