Combining multi‐wavelet and CNN for palmprint recognition against noise and misalignment-Reference-Cited by-同舟云学术

Combining multi‐wavelet and CNN for palmprint recognition against noise and misalignment

Published:2019-06-14 Issue:9 Volume:13 Page:1470-1478
ISSN:1751-9667
Container-title:IET Image Processing
language:en
Short-container-title:IET Image Processing

Author:

Zhou Lijian¹,Guo Han¹,Lin Shanshan¹,Hao Siyuan¹,Zhao Kun¹

Affiliation:

1. School of Information and Control Engineering, Qingdao University of TechnologyQingdaoPeople'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.2018.6122

Reference53 articles.

1. Feature extraction methods for palmpint recognition: a survey and evaluation;Fei L.;IEEE Trans. Syst. Man Cybern. Syst.,2018

2. 2006 The Int. Conf. Advanced Communication Technology Phoenix Park South Korea F. Li M.K.H. Leung X. Yu Palmprint matching using line features 1577 1582

3. 2005 Int. Conf. Image and Graphics Hong Kong X. Wu K. Wang D. Zhang A novel approach of palm‐line extraction 230 233

4. 2005 Int. Conf. Advances in Neural Networks Chongqing China Y. Li K. Wang D. Zhang Palmprint recognition based on translation invariant Zernike moments and modular neural network 177 182

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