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Performance Evaluation of Multimodal Biometric System for Normalization Methods and Classifiers  

Go, Hyoun-Ju (충북대학교 제어계측공학과)
Woo, Na-Young (인하대학교 정보통신공학과)
Shin, Yong-Nyuo (한국정보보호진흥원 정보보호기술단)
Kim, Jae-Sung (한국정보보호진흥원 정보보호기술단)
Kim, Hak-Il (인하대학교 정보통신공학과)
Chun, Myung-Geun (충북대학교 제어계측공학과)
Publication Information
Journal of KIISE:Software and Applications / v.34, no.4, 2007 , pp. 377-388 More about this Journal
Abstract
In this paper, we propose a multi-modal biometric system based on face, iris and fingerprint recognition system. To effectively aggregate two systems, we use statistical distribution models based on matching values for genuine and impostor, respectively. And then, We performed reveal fusion algorithms including weighted summation, Support Vector Machine(SVM), Fisher discriminant analysis, Bayesian classifier. From the various experiments, we found that the performance of multi-modal biometric system was influenced with the normalization methods and classifiers.
Keywords
Multi-modal Biometric Recognition; Face; Fingerprint; Iris Recognition;
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Times Cited By KSCI : 1  (Citation Analysis)
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