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Title: Biometric recognition using entropy-based discretization
Authors: Pathak, AK 
Zhang, DD 
Issue Date: 2007
Source: 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing : proceedings : April 15-20, 2007, Hawaii, Convention Center, Honolulu, Hawaii, U.S.A., 2007, p. II125-II128
Abstract: The biometrics based recognition systems proposed in the literature have not yet exploited user-specific dependencies in the feature level representation. This paper suggests and investigates the performance improvement of the existing biometric systems using the discretization of extracted features. The performance improvement due to the unsupervised and supervised discretization schemes is compared on verity of classifiers; KNN, naïve Bayes, SVM and FFN. The experimental results on the hand-geometry database of 100 users achieve significant improvement in the recognition accuracy and confirm the usefulness of discretization in biometrics systems.
Keywords: Biometrics
Hand geometry
Personal recognition
Feature representation
Feature discretization
Publisher: IEEE
ISBN: 1424407281
Rights: © 2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
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