A novel comparative study using multi-resolution transforms and convolutional neural network (CNN) for contactless palm print verification and identification-Reference-Cited by-同舟云学术

A novel comparative study using multi-resolution transforms and convolutional neural network (CNN) for contactless palm print verification and identification

Published:2020-06-02 Issue:31-32 Volume:79 Page:22929-22963
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Hardalac Firat,Yaşar Hüseyin,Akyel Anil,Kutbay Ugurhan

Funder

None

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-020-09005-2.pdf

Reference61 articles.

1. Ahmad MI, Ilyas MZ, Ngadiran R, Isa MN, Yaakob SN (2014) Palmprint recognition using local and global features. In: International conference on systems, signals and image processing, pp 79–82

2. Bamberger RH, Smith MJ (1992) A filter bank for the directional decomposition of images: theory and design. IEEE Trans Signal Process 40(4):882–93

3. Candes E, Demanet L, Donoho D, Ying L (2006) Fast discrete curvelet transforms. Multiscale Modeling and Simulation 5(3):861–99

4. Candes EJ, Donoho DL (2000) Curvelets: a surprisingly effective nonadaptive representation for objects with edges. Available from: http://www.dtic.mil/dtic/tr/fulltext/u2/p011978.pdf

5. Ceylan M, Yaşar H (2016) A novel approach for automatic blood vessel extraction in retinal images: complex ripplet-I transform and complex valued artificial neural network. Turk J Electr Eng Comput Sci 24(4):3212–27

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