article

Palmprint verification using binary orientation co-occurrence vector

Authors:

Wangmeng ZuoAuthors Info & Claims

Pattern Recognition Letters, Volume 30, Issue 13

Pages 1219 - 1227

https://doi.org/10.1016/j.patrec.2009.05.010

Published: 01 October 2009 Publication History

Abstract

The development of accurate and robust palmprint verification algorithms is a critical issue in automatic palmprint authentication systems. Among various palmprint verification approaches, the orientation based coding methods, such as competitive code (CompCode), palmprint orientation code (POC) and robust line orientation code (RLOC), are state-of-the-art ones. They extract and code the locally dominant orientation as features and could match the input palmprint in real-time and with high accuracy. However, using only one dominant orientation to represent a local region may lose some valuable information because there are cross lines in the palmprint. In this paper, we propose a novel feature extraction algorithm, namely binary orientation co-occurrence vector (BOCV), to represent multiple orientations for a local region. The BOCV can better describe the local orientation features and it is more robust to image rotation. Our experimental results on the public palmprint database show that the proposed BOCV outperforms the CompCode, POC and RLOC by reducing the equal error rate (EER) significantly.

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Cited By

Shao HLiu CLi XZhong D(2024)Privacy Preserving Palmprint Recognition via Federated Metric LearningIEEE Transactions on Information Forensics and Security10.1109/TIFS.2023.332766719(878-891)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TIFS.2023.3327667
Jing KZhang XZhang CLin WMa HPang MWen B(2023)Prototype Correction via Contrastive Augmentation for Few-Shot Unconstrained Palmprint RecognitionIEEE Transactions on Information Forensics and Security10.1109/TIFS.2023.330945818(5431-5446)Online publication date: 28-Aug-2023
https://dl.acm.org/doi/10.1109/TIFS.2023.3309458
Yang ZHuangfu HLeng LZhang BTeoh AZhang Y(2023)Comprehensive Competition Mechanism in Palmprint RecognitionIEEE Transactions on Information Forensics and Security10.1109/TIFS.2023.330610418(5160-5170)Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1109/TIFS.2023.3306104
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Index Terms

Palmprint verification using binary orientation co-occurrence vector
1. Computing methodologies
  1. Computer graphics
    1. Image manipulation
  2. Machine learning
    1. Machine learning algorithms
      1. Feature selection

Index terms have been assigned to the content through auto-classification.

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Published In

cover image Pattern Recognition Letters

Pattern Recognition Letters Volume 30, Issue 13

October, 2009

93 pages

ISSN:0167-8655

Issue’s Table of Contents

Copyright © Elsevier B.V. © 2009.

Publisher

Elsevier Science Inc.

United States

Publication History

Published: 01 October 2009

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Cited By

Shao HLiu CLi XZhong D(2024)Privacy Preserving Palmprint Recognition via Federated Metric LearningIEEE Transactions on Information Forensics and Security10.1109/TIFS.2023.332766719(878-891)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TIFS.2023.3327667
Jing KZhang XZhang CLin WMa HPang MWen B(2023)Prototype Correction via Contrastive Augmentation for Few-Shot Unconstrained Palmprint RecognitionIEEE Transactions on Information Forensics and Security10.1109/TIFS.2023.330945818(5431-5446)Online publication date: 28-Aug-2023
https://dl.acm.org/doi/10.1109/TIFS.2023.3309458
Yang ZHuangfu HLeng LZhang BTeoh AZhang Y(2023)Comprehensive Competition Mechanism in Palmprint RecognitionIEEE Transactions on Information Forensics and Security10.1109/TIFS.2023.330610418(5160-5170)Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1109/TIFS.2023.3306104
Yang ZLeng LTeoh AZhang BZhang Y(2023)Cross-database attack of different coding-based palmprint templatesKnowledge-Based Systems10.1016/j.knosys.2023.110310264:COnline publication date: 15-Mar-2023
https://dl.acm.org/doi/10.1016/j.knosys.2023.110310
Yang ZLeng LMin W(2023)Downsampling in uniformly-spaced windows for coding-based Palmprint recognitionMultimedia Tools and Applications10.1007/s11042-023-14574-z82:15(22981-22996)Online publication date: 21-Feb-2023
https://dl.acm.org/doi/10.1007/s11042-023-14574-z
Yu LYi QZhou K(2023)Multi-scale discriminant representation for generic palmprint recognitionNeural Computing and Applications10.1007/s00521-023-08355-w35:18(13147-13165)Online publication date: 10-Mar-2023
https://dl.acm.org/doi/10.1007/s00521-023-08355-w
Taouche CBelhadef HLaboudi Z(2022)Palmprint Recognition System Based on Multi-Block Local Line Directional Pattern and Feature SelectionInternational Journal of Information Technologies and Systems Approach10.4018/IJITSA.29204215:1(1-26)Online publication date: 11-Mar-2022
https://dl.acm.org/doi/10.4018/IJITSA.292042
Dubey PKanumuri TVyas R(2022)Optimal directional texture codes using multiscale bit crossover count planes for palmprint recognitionMultimedia Tools and Applications10.1007/s11042-022-12580-181:14(20291-20310)Online publication date: 11-Mar-2022
https://dl.acm.org/doi/10.1007/s11042-022-12580-1
Yang ZLeng LZhang BLi MChu J(2022)Two novel style-transfer palmprint reconstruction attacksApplied Intelligence10.1007/s10489-022-03862-053:6(6354-6371)Online publication date: 8-Jul-2022
https://dl.acm.org/doi/10.1007/s10489-022-03862-0
Yang ZLeng LWu TLi MChu J(2022)Multi-order texture features for palmprint recognitionArtificial Intelligence Review10.1007/s10462-022-10194-556:2(995-1011)Online publication date: 2-May-2022
https://dl.acm.org/doi/10.1007/s10462-022-10194-5
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