Hierarchical palmprint feature extraction and recognition based on multi‐wavelets and complex network-Reference-Cited by-同舟云学术

Hierarchical palmprint feature extraction and recognition based on multi‐wavelets and complex network

Published:2018-06 Issue:6 Volume:12 Page:985-992
ISSN:1751-9667
Container-title:IET Image Processing
language:en
Short-container-title:IET Image Processing

Author:

Zhou Lijian¹,Zhang Chen¹,Wang Zuowei¹,Wang Ying²,Lu Zhe‐Ming³

Affiliation:

1. School of Communication and Electronic Engineering, Qingdao University of TechnologyQingdaoPeople's Republic of China

2. SINOPEC Petroleum Exploration and Production Research InstituteBeijingPeople's Republic of China

3. School of Aeronautics and astronautics, Zhejiang UniversityHangzhouPeople's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ipr.2017.0520

Reference21 articles.

1. Palmprint identification algorithm based on energy and direction feature fusion of Gabor wavelet;Qiusheng L.;Chin. J. Sci. Instrum.,2008

2. 2014 Proc. Chinese Conf. on Biometric Recognition Shenyang China D. Hong X. Wu Z. Pan A fast robustness palmprint recognition algorithm biometric recognition 311 318

3. Palmprint feature extraction based on curvelet transform;Liu F.;J. Inf. Hiding Multimedia Signal Process.,2015

4. Palmprint recognition using 2‐D wavelet, ridgelet, curvelet and contourlet;Elaydi H.;i‐Manager's J. Electr. Eng.,2013

5. Wavelets of multiplicity r;Goodman T.N.T.;Trans. Am. Math. Soc.,1994

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