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Palmprint identification and verification with minimal number of features

Palmprint identification and verification with minimal number of features In this paper, palmprint verification and identification with minimum number of features is proposed. The wide principal line extractors (WPLEs) on the region of interest (ROI) are applied to generate wide principal line images (WPLIs). The WPLI is segmented into 2 × 2, 4 × 4, 8 × 8 and 16 × 16 and the feature value is extracted directly from each segment. Experiments are conducted by using the extracted features. The results show that the equal error rate (EER), decidability index (DI) and correct recognition rate (CRR) of the proposed approach is better than existing methods for PolyUPalmprint Database. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Biometrics Inderscience Publishers

Palmprint identification and verification with minimal number of features

International Journal of Biometrics , Volume 10 (1): 13 – Jan 1, 2018

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd
ISSN
1755-8301
eISSN
1755-831X
DOI
10.1504/IJBM.2018.090123
Publisher site
See Article on Publisher Site

Abstract

In this paper, palmprint verification and identification with minimum number of features is proposed. The wide principal line extractors (WPLEs) on the region of interest (ROI) are applied to generate wide principal line images (WPLIs). The WPLI is segmented into 2 × 2, 4 × 4, 8 × 8 and 16 × 16 and the feature value is extracted directly from each segment. Experiments are conducted by using the extracted features. The results show that the equal error rate (EER), decidability index (DI) and correct recognition rate (CRR) of the proposed approach is better than existing methods for PolyUPalmprint Database.

Journal

International Journal of BiometricsInderscience Publishers

Published: Jan 1, 2018

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