Hybrid local phase quantization and grey wolf optimization based SVM for finger vein recognition-Reference-Cited by-同舟云学术

Hybrid local phase quantization and grey wolf optimization based SVM for finger vein recognition

Published:2021-02-02 Issue:10 Volume:80 Page:15233-15271
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Kapoor Kanika,Rani Shalli^ORCID,Kumar Munish,Chopra Vinay,Brar Gubinder Singh

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/s11042-021-10548-1.pdf

Reference69 articles.

1. Akintoye KA, Rahim MSM, Abdullah AH (Feb. 2018) Challenges of finger vein recognition system: a theoretical perspective. International Journal of Emerging Technology and Advanced Engineering 8(2):196–204

2. Asaari MSM, Suandi SA, Rosdi BA (Jun. 2014) Fusion of band limited phase only correlation and width centroid contour distance for finger based biometrics. Expert Syst Appl 41(7):3367–3382

3. Cao K, Jain AK (2018) Automated latent fingerprint recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence

4. Cardoso N, et al (2014) Finger vein recognition using gabor filter and support vector machine. IEEE IPAS’14: International Image Processing Applications AND Systems Conference

5. Changlong H, Zuojin L, Liukui C, Peng J (2017) Identification of finger vein using neural network recognition research based on PCA. IEEE 16th International Conference on Cognitive Informatics & Cognitive Computing:456–460

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