Palm vein recognition method based on fusion of local Gabor histograms

2017 ◽  
Vol 24 (6) ◽  
pp. 55-66 ◽  
Author(s):  
Ma Xin ◽  
Jing Xiaojun
Keyword(s):  
Recognition Method ◽  
Vein Recognition ◽  
Palm Vein

scholarly journals 2D and 3D Palmprint and Palm Vein Recognition Based on Neural Architecture Search

2021 ◽  
Author(s):  
Wei Jia ◽  
Wei Xia ◽  
Yang Zhao ◽  
Hai Min ◽  
Yan-Xiang Chen
Keyword(s):  
Deep Learning ◽  
Recognition Performance ◽  
Research Direction ◽  
Palmprint Recognition ◽  
Neural Architecture ◽  
Development Direction ◽  
Vein Recognition ◽  
Palm Vein ◽  
2D And 3D ◽  
Important Research Direction

AbstractPalmprint recognition and palm vein recognition are two emerging biometrics technologies. In the past two decades, many traditional methods have been proposed for palmprint recognition and palm vein recognition and have achieved impressive results. In recent years, in the field of artificial intelligence, deep learning has gradually become the mainstream recognition technology because of its excellent recognition performance. Some researchers have tried to use convolutional neural networks (CNNs) for palmprint recognition and palm vein recognition. However, the architectures of these CNNs have mostly been developed manually by human experts, which is a time-consuming and error-prone process. In order to overcome some shortcomings of manually designed CNN, neural architecture search (NAS) technology has become an important research direction of deep learning. The significance of NAS is to solve the deep learning model’s parameter adjustment problem, which is a cross-study combining optimization and machine learning. NAS technology represents the future development direction of deep learning. However, up to now, NAS technology has not been well studied for palmprint recognition and palm vein recognition. In this paper, in order to investigate the problem of NAS-based 2D and 3D palmprint recognition and palm vein recognition in-depth, we conduct a performance evaluation of twenty representative NAS methods on five 2D palmprint databases, two palm vein databases, and one 3D palmprint database. Experimental results show that some NAS methods can achieve promising recognition results. Remarkably, among different evaluated NAS methods, ProxylessNAS achieves the best recognition performance.

Palm Vein Recognition Based on Independent Component Analysis

2013 ◽  
Vol 333-335 ◽  
pp. 1106-1109
Author(s):  
Wei Wu
Keyword(s):  
Pattern Recognition ◽  
Independent Component Analysis ◽  
Euclidean Distance ◽  
Recognition Performance ◽  
Component Analysis ◽  
Independent Component ◽  
Experimental Results ◽  
Vein Pattern ◽  
Vein Recognition ◽  
Palm Vein

Palm vein pattern recognition is one of the newest biometric techniques researched today. This paper proposes project the palm vein image matrix based on independent component analysis directly, then calculates the Euclidean distance of the projection matrix, seeks the nearest distance for classification. The experiment has been done in a self-build palm vein database. Experimental results show that the algorithm of independent component analysis is suitable for palm vein recognition and the recognition performance is practical.

A Contactless Palm Vein Recognition System Based on Principle Line SIFT

2013 ◽  
Vol 347-350 ◽  
pp. 3469-3472 ◽  
Author(s):  
Wei Wu ◽  
Sen Lin ◽  
Hui Song
Keyword(s):  
Traditional Method ◽  
Recognition System ◽  
Scale Invariant ◽  
Limited Effect ◽  
Image Deformation ◽  
Invariant Feature ◽  
Feature Transform ◽  
Vein Recognition ◽  
Palm Vein ◽  
Scale Invariant Feature

Compared with the traditional method of contact collection, contactless acquisition is the mainstream and trend of palm vein recognition. However, this method may lead to image deformation caused by no parallel of the palm plane and the sensor plane. In order to improve the limited effect of Scale Invariant Feature Transform (SIFT) about this problem, a better method of palm vein recognition which based on principle line SIFT is proposed. Based on the self-built database, this method is compared with the SIFT and other typical palm vein recognition methods, the experimental results show that our system can achieve the best performance.

A New Location Method of ROI for Contactless Palm Vein Recognition

2013 ◽  
Vol 760-762 ◽  
pp. 1398-1401
Author(s):  
Wei Wu ◽  
Wei Qi Yuan ◽  
Hui Song
Keyword(s):  
Pattern Recognition ◽  
Recognition Rate ◽  
New Method ◽  
Vein Pattern ◽  
Location Method ◽  
Vein Recognition ◽  
Palm Vein ◽  
New Location

Palm vein pattern recognition is one of the newest biometric techniques researched today.At present, literatures selecte the center of the palm as the ROI of palm vein recognition. However the vein image in this area is not clear in some peoples palm. In this paper, we proposed a new location method of ROI which takes thenar area as the ROI. In the experiment part, it compares the recognition rate between the new and the traditional ROI in self-established contactless palm vein database. The result shows that this new method has got the recognition rate of 98.9258% and has increased recognition rate 2.0911% compared with the traditional one.

scholarly journals Review of palm vein recognition

2019 ◽  
Vol 9 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Wei Wu ◽  
Stephen John Elliott ◽  
Sen Lin ◽  
Shenshen Sun ◽  
Yandong Tang
Keyword(s):  
Vein Recognition ◽  
Palm Vein
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