Ffv-Mbc: A Novel Fused Finger-Vein Recognition Method Based on Monogenic Binary Coding

2022 ◽  
Author(s):  
Zhiyong Tao ◽  
Meng Wang ◽  
Xinru Zhou ◽  
Jie Li ◽  
Sen Lin
Keyword(s):  
Recognition Method ◽  
Finger Vein ◽  
Binary Coding ◽  
Vein Recognition ◽  
Finger Vein Recognition

scholarly journals A Finger Vein Recognition Method Using Improved Oriented Filter and Elastic Registration

2013 ◽  
Vol 6 (7) ◽  
pp. 1153-1159 ◽  
Author(s):  
Ma Hui ◽  
Popoola Oluwatoyin P. ◽  
Sun Shuli
Keyword(s):  
Recognition Method ◽  
Elastic Registration ◽  
Finger Vein ◽  
Vein Recognition ◽  
Finger Vein Recognition

Finger Vein Recognition Based on Stable and Discriminative Superpixels

2016 ◽  
Vol 30 (06) ◽  
pp. 1650015 ◽  
Author(s):  
Lizhen Zhou ◽  
Gongping Yang ◽  
Yilong Yin ◽  
Lu Yang ◽  
Kuikui Wang
Keyword(s):  
Recognition Performance ◽  
Fusion Method ◽  
Recognition Method ◽  
Biometric Technology ◽  
Training Images ◽  
Finger Vein ◽  
Vein Recognition ◽  
Matching Score ◽  
Finger Vein Recognition ◽  
Better Than

Finger vein pattern, as a promising hand-based biometric technology, has been well studied in recent years. In this paper, a new superpixel-based finger vein recognition method is presented. In the proposed method, we develop two types of effective superpixels, i.e. stable superpixel and discriminative superpixel to represent finger vein image and these superpixels are expected to play different roles in matching stage. In detail, the stable and discriminative superpixels are firstly learned from the training images for each enrolled class. When verifying a testing image, we just compare the superpixels at the same location as the two types of superpixels in template. Then, the two types of superpixels are combined utilizing a reversible weight-based fusion method in score level. Additionally, to further improve the recognition performance, we explore the superpixel context feature (SPCF). For each superpixel the SPCF is obtained by comparing the current superpixel with its surrounding neighbors. In the final matching stage, we integrate the matching score of two types of superpixels and it of the SPCF using the weighted SUM fusion method. The experimental results on two open finger vein databases, i.e. PolyU and SDUMLA-FV, show that our method not only performs better than the existing superpixel-based method, but also has advantages in comparison with some traditional ones.

A New Finger Vein Recognition Method Based on the Difference Symmetric Local Graph Structure (DSLGS)

2015 ◽  
Vol 8 (10) ◽  
pp. 71-80 ◽  
Author(s):  
Song Dong ◽  
Jucheng Yang ◽  
Chao Wang ◽  
Yarui Chen ◽  
Di Sun
Keyword(s):  
Graph Structure ◽  
Recognition Method ◽  
Finger Vein ◽  
Local Graph ◽  
The Difference ◽  
Vein Recognition ◽  
Finger Vein Recognition
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