Multi-algorithm Feature Level Fusion Using Finger Knuckle Print Biometric

Al Mahafzah, Harbi and Imran, Mohammad and Sheshadri, H. S. (2012) Multi-algorithm Feature Level Fusion Using Finger Knuckle Print Biometric. In: Computer Applications for Communication, Networking, and Digital Contents. Communications in Computer and Information Science, 350 . Springer Berlin Heidelberg, pp. 302-311. ISBN 978-3-642-35593-6

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Official URL: http://dx.doi.org/10.1007/978-3-642-35594-3_42

Abstract

This paper proposed the use of multi-algorithm feature level fusion as a means to improve the performance of Finger Knuckle Print (FKP) verification. LG, LPQ, PCA, and LPP have been used to extract the FKP features. Experiments are performed using the FKP database, which consists of 7,920 images. Results indicate that the multi-algorithm verification approach outperforms higher performance than using any single algorithm. The biometric performance using feature level fusions under different normalization technique as well have been demonstrated in this paper.

Item Type: Book Section
Additional Information: Unmapped bibliographic data: SE - 42 [Field not mapped to EPrints]
Uncontrolled Keywords: Feature Level Fusion, Multi-Biometric, Multi-Algorithm, Normalization
Subjects: Information, Computer and Applied Sciences > Computer Science
Divisions: PG Campuses > Manasagangotri, Mysore > Computer Science
Depositing User: Kodandarama
Date Deposited: 20 Jun 2013 10:25
Last Modified: 26 Oct 2015 07:31
URI: http://eprints.uni-mysore.ac.in/id/eprint/12798

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