Enhanced Gabor-based region covariance matrices for palmprint recognition

J. Lu; Y. Zhao; J. Hu

doi:10.1049/el.2009.0871

Enhanced Gabor-based region covariance matrices for palmprint recognition

J. Lu^*
, Y. Zhao
, J. Hu

^*Corresponding author for this work

Nanyang Technological University
Xi'an University of Technology

Research output: Contribution to journal › Article › peer-review

30 Scopus citations

Abstract

An enhanced Gabor-based region covariance matrices (EGRCM) method for palmprint recognition is proposed. Motivated by the fact that both the Gabor magnitude (GM) and the Gabor phase (GP) of a certain image contain effective information for image feature extraction, they are utilised simultaneously to construct the proposed EGRCM image descriptor for palmprint recognition. Experimental results demonstrate the efficacy of the proposed method.

Original language	English
Pages (from-to)	880-881
Number of pages	2
Journal	Electronics Letters
Volume	45
Issue number	17
DOIs	https://doi.org/10.1049/el.2009.0871
State	Published - 2009
Externally published	Yes

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10.1049/el.2009.0871

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title = "Enhanced Gabor-based region covariance matrices for palmprint recognition",

abstract = "An enhanced Gabor-based region covariance matrices (EGRCM) method for palmprint recognition is proposed. Motivated by the fact that both the Gabor magnitude (GM) and the Gabor phase (GP) of a certain image contain effective information for image feature extraction, they are utilised simultaneously to construct the proposed EGRCM image descriptor for palmprint recognition. Experimental results demonstrate the efficacy of the proposed method.",

author = "J. Lu and Y. Zhao and J. Hu",

year = "2009",

doi = "10.1049/el.2009.0871",

language = "英语",

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AU - Hu, J.

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AB - An enhanced Gabor-based region covariance matrices (EGRCM) method for palmprint recognition is proposed. Motivated by the fact that both the Gabor magnitude (GM) and the Gabor phase (GP) of a certain image contain effective information for image feature extraction, they are utilised simultaneously to construct the proposed EGRCM image descriptor for palmprint recognition. Experimental results demonstrate the efficacy of the proposed method.

UR - https://www.scopus.com/pages/publications/68949119819

U2 - 10.1049/el.2009.0871

DO - 10.1049/el.2009.0871

M3 - 文章

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SN - 0013-5194

VL - 45

SP - 880

EP - 881

JO - Electronics Letters

JF - Electronics Letters

IS - 17

ER -

Enhanced Gabor-based region covariance matrices for palmprint recognition

Abstract

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