Literature DB >> 22945174

Finger vein verification system based on sparse representation.

Yang Xin1, Zhi Liu, Haixia Zhang, Hong Zhang.   

Abstract

Finger vein verification is a promising biometric pattern for personal identification in terms of security and convenience. The recognition performance of this technology heavily relies on the quality of finger vein images and on the recognition algorithm. To achieve efficient recognition performance, a special finger vein imaging device is developed, and a finger vein recognition method based on sparse representation is proposed. The motivation for the proposed method is that finger vein images exhibit a sparse property. In the proposed system, the regions of interest (ROIs) in the finger vein images are segmented and enhanced. Sparse representation and sparsity preserving projection on ROIs are performed to obtain the features. Finally, the features are measured for recognition. An equal error rate of 0.017% was achieved based on the finger vein image database, which contains images that were captured by using the near-IR imaging device that was developed in this study. The experimental results demonstrate that the proposed method is faster and more robust than previous methods.

Mesh:

Year:  2012        PMID: 22945174     DOI: 10.1364/AO.51.006252

Source DB:  PubMed          Journal:  Appl Opt        ISSN: 1559-128X            Impact factor:   1.980


  3 in total

1.  Real-Time Remote Health Monitoring Systems Using Body Sensor Information and Finger Vein Biometric Verification: A Multi-Layer Systematic Review.

Authors:  A H Mohsin; A A Zaidan; B B Zaidan; A S Albahri; O S Albahri; M A Alsalem; K I Mohammed
Journal:  J Med Syst       Date:  2018-10-16       Impact factor: 4.460

2.  Robust finger vein ROI localization based on flexible segmentation.

Authors:  Yu Lu; Shan Juan Xie; Sook Yoon; Jucheng Yang; Dong Sun Park
Journal:  Sensors (Basel)       Date:  2013-10-24       Impact factor: 3.576

3.  A Simple and Efficient Method for Finger Vein Recognition.

Authors:  Zhongxia Zhang; Mingwen Wang
Journal:  Sensors (Basel)       Date:  2022-03-14       Impact factor: 3.576

  3 in total

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