scholarly journals Improving hand vein recognition by score weighted fusion of wavelet-domain multi-radius local binary patterns

2016 ◽  
Vol 54 (3) ◽  
pp. 151 ◽  
Author(s):  
Di Huang ◽  
Lik Kwan Shark ◽  
Yiding Wang ◽  
Qiangyu Duan
Keyword(s):  
Local Binary Patterns ◽  
Wavelet Domain ◽  
Weighted Fusion ◽  
Hand Vein ◽  
Vein Recognition

A New Preprocessing Algorithm of Hand Vein Image

2013 ◽  
Vol 462-463 ◽  
pp. 312-315
Author(s):  
Cai Xia Liu
Keyword(s):  
Wavelet Decomposition ◽  
Feature Recognition ◽  
Hot Spot ◽  
Low Frequency ◽  
Histogram Equalization ◽  
Segmentation Algorithm ◽  
Human Hand ◽  
Security Technology ◽  
Hand Vein ◽  
Vein Recognition

Biometrics technology is an important security technology and the research of it has become a new hot spot for its superior security features. Then hand vein recognition is a new biological feature recognition which has many advantages, such as safety, non-contact. According to the features of human hand vein image, a hand vein preprocessing method based on wavelet transform and windows maximum between-class difference method threshold (OTSU) segmentation algorithm is proposed. In this paper, the hand vein image is enhanced by adaptive histogram equalization in low frequency part of the hand vein image after wavelet decomposition and filtering before feature extraction. Then the windows OTSU threshold segmentation algorithm is used to get the features. The experimental results show that this method is simple and easy to realize and has laid a good foundation for the latter part of the vein recognition.

Hand Vein Recognition Based on Feature Fusion

2014 ◽  
Vol 43 (1) ◽  
pp. 110004
Author(s):  
胡云朋 HU Yun-peng ◽  
王志勇 WANG Zhi-yong ◽  
李飞 LI Fei ◽  
杨晓苹 YANG Xiao-ping ◽  
薛玉明 XUE Yu-ming
Keyword(s):  
Feature Fusion ◽  
Hand Vein ◽  
Vein Recognition

scholarly journals Recognition of Dorsal Hand Vein Based Bit Planes and Block Mutual Information

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3718 ◽  
Author(s):  
Yiding Wang ◽  
Heng Cao ◽  
Xiaochen Jiang ◽  
Yuanyan Tang
Keyword(s):  
Mutual Information ◽  
Recognition Rate ◽  
Scale Invariant ◽  
Dorsal Hand ◽  
Hand Vein ◽  
Bit Plane ◽  
Vein Recognition ◽  
Dorsal Hand Vein ◽  
Bit Planes ◽  
Dorsal Hand Vein Recognition

The dorsal hand vein images captured by cross-device may have great differences in brightness, displacement, rotation angle and size. These deviations must influence greatly the results of dorsal hand vein recognition. To solve these problems, the method of dorsal hand vein recognition was put forward based on bit plane and block mutual information in this paper. Firstly, the input gray image of dorsal hand vein was converted to eight-bit planes to overcome the interference of brightness inside the higher bit planes and the interference of noise inside the lower bit planes. Secondly, the texture of each bit plane of dorsal hand vein was described by a block method and the mutual information between blocks was calculated as texture features by three kinds of modes to solve the problem of rotation and size. Finally, the experiments cross-device were carried out. One device was used to be registered, the other was used to recognize. Compared with the SIFT (Scale-invariant feature transform, SIFT) algorithm, the new algorithm can increase the recognition rate of dorsal hand vein from 86.60% to 93.33%.

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