Multibiometric: Feature Level Fusion Using FKP Multi-Instance biometric
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.
Keywords: Multi-Biometric; Multi-Instance; Feature Level Fusion, Normalization
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ABOUT THE AUTHORS
Harbi Almahafzah
Research Scholar, P,E,T, Foundation Research, University of Mysore, Mandya, India
Mohammad Imran
Research Scholar, Department of Study in Computer Science, University of Mysore, Mysore, India
H.S. Sheshadri
Prof.Department E & C Engg, P.E.S College of Engineering, V.T.U, Mandya, India
Harbi Almahafzah
Research Scholar, P,E,T, Foundation Research, University of Mysore, Mandya, India
Mohammad Imran
Research Scholar, Department of Study in Computer Science, University of Mysore, Mysore, India
H.S. Sheshadri
Prof.Department E & C Engg, P.E.S College of Engineering, V.T.U, Mandya, India
