Laser & Optoelectronics Progress, Volume. 58, Issue 2, 0210019(2021)

Finger-Knuckle-Print Recognition Based on NSST and Tetrolet Energy Features

Yuan Wang* and Sen Lin
Author Affiliations
  • School of Electronic and Information Engineering, Liaoning Technical University, Huludao, Liaoning 125105, China
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    References(20)

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    [11] Kumar A, Wang B C. Recovering and matching minutiae patterns from finger knuckle images[J]. Pattern Recognition Letters, 68, 361-367(2015).

    [12] Nigam A, Tiwari K, Gupta P. Multiple texture information fusion for finger-knuckle-print authentication system[J]. Neurocomputing, 188, 190-205(2016).

    [13] Liu Y H, Yan D Q, Wang H D. Medical image registration method based on non-subsampled shearlet transform[J]. Application Research of Computers, 32, 1586-1588(2015).

    [15] Zhang L H. The research on image enhancement algorithm based on NSST and Tetrolet transform[D]. Urumqi: Xinjiang University(2018).

    [16] Zhang Y J, Wu H Y[J]. A NSST based adaptive threshold image denoising method China Computer & Communication, 2015, 12-15.

    [19] Zhang L, Zhang L, Zhang D et al. Ensemble of local and global information for finger-knuckle-print recognition[J]. Pattern Recognition, 44, 1990-1998(2011).

    [20] Zhang L, Zhang L, Zhang D et al. Phase congruency induced local features for finger-knuckle-print recognition[J]. Pattern Recognition, 45, 2522-2531(2012).

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    Yuan Wang, Sen Lin. Finger-Knuckle-Print Recognition Based on NSST and Tetrolet Energy Features[J]. Laser & Optoelectronics Progress, 2021, 58(2): 0210019

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    Paper Information

    Category: Image Processing

    Received: Jun. 17, 2020

    Accepted: Jul. 20, 2020

    Published Online: Jan. 11, 2021

    The Author Email: Wang Yuan (826998554@qq.com)

    DOI:10.3788/LOP202158.0210019

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