Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/205
Title: Biometric recognition using entropy-based discretization
Authors: Pathak, Ajay Kumar
Zhang, David D.
Subjects: Biometrics
Hand geometry
Personal recognition
Feature representation
Feature discretization
Issue Date: 2007
Publisher: IEEE
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.
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Type: Conference Paper
URI: http://hdl.handle.net/10397/205
ISBN: 1424407281
Appears in Collections:COMP Conference Papers & Presentations

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