research-article

A Comparative Study of Palmprint Recognition Algorithms

Authors:

Feng YueAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 44, Issue 1

Article No.: 2, Pages 1 - 37

https://doi.org/10.1145/2071389.2071391

Published: 01 January 2012 Publication History

Abstract

Palmprint images contain rich unique features for reliable human identification, which makes it a very competitive topic in biometric research. A great many different low resolution palmprint recognition algorithms have been developed, which can be roughly grouped into three categories: holistic-based, feature-based, and hybrid methods. The purpose of this article is to provide an updated survey of palmprint recognition methods, and present a comparative study to evaluate the performance of the state-of-the-art palmprint recognition methods. Using the Hong Kong Polytechnic University (HKPU) palmprint database (version 2), we compare the recognition performance of a number of holistic-based (Fisherpalms and DCT+LDA) and local feature-based (competitive code, ordinal code, robust line orientation code, derivative of Gaussian code, and wide line detector) methods, and then investigate the error correlation and score-level fusion performance of different algorithms. After discussing the achievements and limitations of current palmprint recognition algorithms, we conclude with providing several potential research directions for the future.

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Index Terms

A Comparative Study of Palmprint Recognition Algorithms
1. Computing methodologies
2. General and reference
  1. Document types
    1. Surveys and overviews

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Published In

cover image ACM Computing Surveys

ACM Computing Surveys Volume 44, Issue 1

January 2012

181 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/2071389

Issue’s Table of Contents

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 January 2012

Accepted: 01 April 2010

Received: 01 July 2008

Published in CSUR Volume 44, Issue 1

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Qu Y(2024)Image enhancement optimization of resnet convolutional neural network for palmprint recognitionInternational Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024)10.1117/12.3033501(15)Online publication date: 13-Jun-2024
https://doi.org/10.1117/12.3033501
Fan DLiang XJia WZhang D(2024)Toward Large-Scale Palmprint Image Analysis by a Rich Orientation CodeIEEE Transactions on Systems, Man, and Cybernetics: Systems10.1109/TSMC.2024.337753554:7(4113-4125)Online publication date: Jul-2024
https://doi.org/10.1109/TSMC.2024.3377535
Wu YHu J(2024)Deep and Shallow Feature Fusion in Feature Score Level for Palmprint RecognitionIET Biometrics10.1049/2024/56835472024:1Online publication date: 22-Oct-2024
https://doi.org/10.1049/2024/5683547
Cao ZZhao WZhao HPang L(2024)Composite fixed-length ordered features with index-of-max transformation for high-performing and secure palmprint template protectionJournal of Information and Intelligence10.1016/j.jiixd.2024.09.002Online publication date: Sep-2024
https://doi.org/10.1016/j.jiixd.2024.09.002
Lai YWan GQin X(2024)Decoding China's new-type industrialization: Insights from an XGBoost-SHAP analysisJournal of Cleaner Production10.1016/j.jclepro.2024.143927478(143927)Online publication date: Nov-2024
https://doi.org/10.1016/j.jclepro.2024.143927
Khan MLi HZhao C(2024)Deep secure PalmNet: A novel cancelable palmprint template protection scheme with deep attention net and randomized hashing security mechanismComputers & Security10.1016/j.cose.2024.103863142(103863)Online publication date: Jul-2024
https://doi.org/10.1016/j.cose.2024.103863
Yi JJiang HWang XTan Y(2024)A Comprehensive Review on Sparse Representation and Compressed Perception in Optical Image ReconstructionArchives of Computational Methods in Engineering10.1007/s11831-024-10071-0Online publication date: 1-Mar-2024
https://doi.org/10.1007/s11831-024-10071-0
Guerrache FHaddadou H(2024)A quality-based context-switching framework for palmprint recognitionMultimedia Tools and Applications10.1007/s11042-024-19867-5Online publication date: 1-Aug-2024
https://doi.org/10.1007/s11042-024-19867-5
Amrouni NBenzaoui AZeroual A(2023)Palmprint Recognition: Extensive Exploration of Databases, Methodologies, Comparative Assessment, and Future DirectionsApplied Sciences10.3390/app1401015314:1(153)Online publication date: 23-Dec-2023
https://doi.org/10.3390/app14010153
Mohamed Abdul Cader ABanks JChandran V(2023)Invariant Feature Encoding for Contact Handprints Using Delaunay Triangulated GraphApplied Sciences10.3390/app13191087413:19(10874)Online publication date: 30-Sep-2023
https://doi.org/10.3390/app131910874
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