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International Journal of Scientific and Engineering Research
ISSN Online 2229-5518
ISSN Print: 2229-5518 6    
Website: http://www.ijser.org
scirp IJSER >> Volume 3,Issue 6,June 2012
Improving Biometric Identification Through Score Level Face Fingerprint Fusion
Full Text(PDF, )  PP.792-795  
Author(s)
Mrs. Smita Kulkarni
KEYWORDS
Multimodal biometrics, score level fusion, verification, normalization, sum rule, Support Vector Machines
ABSTRACT
Multi-modal biometric fusion is more accurate and reliable compared to recognition using a single biometric modality. However, most exist-ing fusion approaches neglect the influence of the qualities of the biometric samples in information fusion. Our goal is to advance the state-of-the-art in biometric fusion technology by providing a more universal and more accurate solution for personal identification and verification with predictive quality metrics. In this work, we developed score-level multi-modal fusion algorithms based on predictive quality metrics and employed them for the task of face and fingerprint biometric fusion In this paper the performance of sum rule-based score level fusion are examined. Before fusion of sum rule, normalization is done by using any one technique like min-max normalization, z score normalization and tanh estimator's normalization. In this paper min max normalization is used for normalization.
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