A real time embedded novel finger-vein recognition system for authenticated on teller machine

2012 ◽  
Author(s):  
P. Harsha ◽  
C. Subashini
Keyword(s):  
Real Time ◽  
Recognition System ◽  
Finger Vein ◽  
Vein Recognition ◽  
Finger Vein Recognition

A Real Time of an Automatic Finger Vein Recognition System

2018 ◽  
Vol 28 (3) ◽  
pp. 430-438 ◽  
Author(s):  
Randa Boukhris Trabelsi ◽  
Alima Damak Masmoudi ◽  
Dorra Sellami Masmoudi
Keyword(s):  
Real Time ◽  
Recognition System ◽  
Finger Vein ◽  
Vein Recognition ◽  
Finger Vein Recognition

scholarly journals Finger-Vein Recognition Using Heterogeneous Databases by Domain Adaption Based on a Cycle-Consistent Adversarial Network

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 524
Author(s):  
Kyoung Jun Noh ◽  
Jiho Choi ◽  
Jin Seong Hong ◽  
Kang Ryoung Park
Keyword(s):  
Domain Adaptation ◽  
Recognition Accuracy ◽  
Recognition System ◽  
Heterogeneous Databases ◽  
Second Best ◽  
Finger Vein ◽  
Adversarial Network ◽  
Image Characteristics ◽  
Vein Recognition ◽  
Finger Vein Recognition

The conventional finger-vein recognition system is trained using one type of database and entails the serious problem of performance degradation when tested with different types of databases. This degradation is caused by changes in image characteristics due to variable factors such as position of camera, finger, and lighting. Therefore, each database has varying characteristics despite the same finger-vein modality. However, previous researches on improving the recognition accuracy of unobserved or heterogeneous databases is lacking. To overcome this problem, we propose a method to improve the finger-vein recognition accuracy using domain adaptation between heterogeneous databases using cycle-consistent adversarial networks (CycleGAN), which enhances the recognition accuracy of unobserved data. The experiments were performed with two open databases—Shandong University homologous multi-modal traits finger-vein database (SDUMLA-HMT-DB) and Hong Kong Polytech University finger-image database (HKPolyU-DB). They showed that the equal error rate (EER) of finger-vein recognition was 0.85% in case of training with SDUMLA-HMT-DB and testing with HKPolyU-DB, which had an improvement of 33.1% compared to the second best method. The EER was 3.4% in case of training with HKPolyU-DB and testing with SDUMLA-HMT-DB, which also had an improvement of 4.8% compared to the second best method.

An Arcloss-Based and Openset-Test-Oriented Finger Vein Recognition System

2021 ◽  
pp. 287-294
Author(s):  
Zhenxiang Chen ◽  
Wangwang Yu ◽  
Haohan Bai ◽  
Yongjie Li
Keyword(s):  
Recognition System ◽  
Finger Vein ◽  
Vein Recognition ◽  
Finger Vein Recognition

scholarly journals Fast Finger Vein Recognition Based on Sparse Matching Algorithm under a Multicore Platform for Real-Time Individuals Identification

Symmetry ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1167
Author(s):  
Ruber Hernández-García ◽  
Ricardo J. Barrientos ◽  
Cristofher Rojas ◽  
Wladimir E. Soto-Silva ◽  
Marco Mora ◽  
...  
Keyword(s):  
Real Time ◽  
State Of The Art ◽  
Individual Identification ◽  
Affine Transformations ◽  
Private Companies ◽  
Time Efficiency ◽  
Finger Vein ◽  
Vein Recognition ◽  
Coarse To Fine ◽  
Finger Vein Recognition

Nowadays, individual identification is a problem in many private companies, but also in governmental and public order entities. Currently, there are multiple biometric methods, each with different advantages. Finger vein recognition is a modern biometric technique, which has several advantages, especially in terms of security and accuracy. However, image deformations and time efficiency are two of the major limitations of state-of-the-art contributions. In spite of affine transformations produced during the acquisition process, the geometric structure of finger vein images remains invariant. This consideration of the symmetry phenomena presented in finger vein images is exploited in the present work. We combine an image enhancement procedure, the DAISY descriptor, and an optimized Coarse-to-fine PatchMatch (CPM) algorithm under a multicore parallel platform, to develop a fast finger vein recognition method for real-time individuals identification. Our proposal provides an effective and efficient technique to obtain the displacement between finger vein images and considering it as discriminatory information. Experimental results on two well-known databases, PolyU and SDUMLA, show that our proposed approach achieves results comparable to deformation-based techniques of the state-of-the-art, finding statistical differences respect to non-deformation-based approaches. Moreover, our method highly outperforms the baseline method in time efficiency.

Near Infrared Finger Vein Recognition Method Based on Subspace Projection Technology

2014 ◽  
Vol 1030-1032 ◽  
pp. 2382-2385 ◽  
Author(s):  
Lin Lin Fan ◽  
Hui Ma ◽  
Ke Jun Wang ◽  
Yong Liang Shen ◽  
Ying Shi ◽  
...  
Keyword(s):  
Near Infrared ◽  
Nearest Neighbor ◽  
Recognition Performance ◽  
Recognition System ◽  
Critical Issue ◽  
Subspace Projection ◽  
Threshold Method ◽  
Finger Vein ◽  
Vein Recognition ◽  
Finger Vein Recognition

Finger vein recognition refers to a recent biometric technique which exploits the vein patterns in the human finger to identify individuals. Finger vein recognition faces a number of challenges. One critical issue is the performance of finger vein recognition system. To overcome this problem, a finger vein recognition algorithm based on one kind of subspace projection technology is presented. Firstly, we use Kapur entropy threshold method to achieve the purpose of intercepting region of finger under contactless mode. Then the finger vein features were extracted by 2DPCA method. Finally, we used of nearest neighbor distance classifier for matching. The results indicate that the algorithm has good recognition performance.

Real-Time Finger-Vein Recognition for Security and Monitoring System

2014 ◽  
Vol 550 ◽  
pp. 194-203
Author(s):  
S. Nandhini ◽  
D. Shyam
Keyword(s):  
Private Information ◽  
Electronic Devices ◽  
Recognition System ◽  
Biometric Authentication ◽  
Finger Vein ◽  
Security Authentication ◽  
Consumer Electronic ◽  
Authentication System ◽  
Vein Recognition ◽  
Finger Vein Recognition

— The demand for simple, convenient and high security authentication systems protecting private information is rising with the development of improved consumer electronic devices. In existing systems cards, pin numbers and passwords are used for authentication. However theft of cards and guessing of pin numbers and passwords by exploiters is a serial threat. Hence the need to protect private information by means of biometric solutions is very essential. The proposed system finger vein recognition system is a biometric authentication system. The maximum curvature method of feature extraction used here extracts the centrelines without being affected by fluctuations in vein width and brightness. The results of processing are sent using GSM to owners or administrators. The system can be used for application such as bank ATM identification and verification, automatic door locking control systems and automated attendance register system.

Sign in / Sign up

Export Citation Format

Share Document