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CMC curve properties and biometric source weighting in multi-biometric score-level fusion

: Damer, Naser; Opel, Alexander; Nouak, Alexander

Institute of Electrical and Electronics Engineers -IEEE-; International Society of Information Fusion -ISIF-:
FUSION 2014, 17th International Conference on Information Fusion : 7 -10 July 2014, Salamanca, Spain
Piscataway, NJ: IEEE, 2014
ISBN: 978-1-4799-1634-4
ISBN: 9788490123553
6 pp.
International Conference on Information Fusion (FUSION) <17, 2014, Salamanca>
Conference Paper
Fraunhofer IGD ()
multi-biometrics; pattern recognition; face recognition; fingerprint recognition; robustness; database; Business Field: Visual decision support; Business Field: Digital society; Research Area: Computer vision (CV)

Multi-biometrics tries to build a unified biometric decision based on multiple biometric sources in an effort to gain more accuracy and robustness. Multi-biometric fusion aims at optimally combining the information produced by the multiple biometric sources, this usually requires assigning relative weights for the biometric sources to optimize their effect on the final decision. This work presents a new approach for biometric sources weighting within a score-level multi-biometric system. The presented solution tries to investigate the properties of the cumulative match characteristic (CMC) curve, which represents the biometric performance under the identification scenario, and extract biometric source weights based on those properties. The proposed solution is evaluated along with a set of state of the art and best practice weighting techniques. The evaluation was performed on the Biometric Scores Set BSSR1 database and a satisfying and stable performance was achieved.