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International Journal of Machine Learning and Cybernetics
Published in: International Journal of Machine Learning and Cybernetics 7/2020

18-12-2019 | Original Article

Orientation space code and multi-feature two-phase sparse representation for palmprint recognition

Authors: Lu Liang, Tao Chen, Lunke Fei

Published in: International Journal of Machine Learning and Cybernetics | Issue 7/2020

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Abstract

Orientation based coding method is one of the most important approaches in palmprint recognition, which achieves impressive performance by extracting one or more dominant orientation features, and calculating the distance between features of two palmprints. However, simply using the orientation features may be vulnerable to noisy and rotation. In this paper, we proposed a novel orientation-space code scheme to represent the orientation space feature of palmprint and designed a novel multi-feature two-phase sparse representation (MTPSR) scheme for feature matching. Extensive experiments on three benchmark palmprint databases are conducted to demonstrate the high effectiveness of the proposed method
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Metadata
Title
Orientation space code and multi-feature two-phase sparse representation for palmprint recognition
Authors
Lu Liang
Tao Chen
Lunke Fei
Publication date
18-12-2019
Publisher
Springer Berlin Heidelberg
Published in
International Journal of Machine Learning and Cybernetics / Issue 7/2020
Print ISSN: 1868-8071
Electronic ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-019-01049-7

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