A Finger-vein Biometric System Based on Textural Features

2018 ◽  
pp. 367-375
Author(s):  
Enrique V. Carrera ◽  
Santiago Izurieta ◽  
Ricardo Carrera
Keyword(s):  
Textural Features ◽  
Biometric System ◽  
Finger Vein

Multimodal biometric system using deep learning based on face and finger vein fusion

2021 ◽  
pp. 1-13
Author(s):  
Shikhar Tyagi ◽  
Bhavya Chawla ◽  
Rupav Jain ◽  
Smriti Srivastava
Keyword(s):  
High Performance ◽  
Recognition Accuracy ◽  
Error Rates ◽  
Facial Features ◽  
Biometric System ◽  
Deep Convolutional Neural Networks ◽  
Finger Vein ◽  
Biometric Systems ◽  
Overall Performance ◽  
Recognition Systems

Single biometric modalities like facial features and vein patterns despite being reliable characteristics show limitations that restrict them from offering high performance and robustness. Multimodal biometric systems have gained interest due to their ability to overcome the inherent limitations of the underlying single biometric modalities and generally have been shown to improve the overall performance for identification and recognition purposes. This paper proposes highly accurate and robust multimodal biometric identification as well as recognition systems based on fusion of face and finger vein modalities. The feature extraction for both face and finger vein is carried out by exploiting deep convolutional neural networks. The fusion process involves combining the extracted relevant features from the two modalities at score level. The experimental results over all considered public databases show a significant improvement in terms of identification and recognition accuracy as well as equal error rates.

scholarly journals Biometric, Fingervein, Machine L Implementation of a Security System, Using Captured Fingervein, Applying the Concepts of Machine Learning

2020 ◽  
Vol 9 (04) ◽  
pp. 24994-25007
Author(s):  
Oyinloye Oghenerukevwe Elohor ◽  
Akinbohun Folake ◽  
Thompson Aderonke ◽  
Korede Bashir
Keyword(s):  
Machine Learning ◽  
Near Infrared ◽  
Accurate Solution ◽  
Great Promise ◽  
Biometric System ◽  
Finger Vein ◽  
Similarities And Differences ◽  
Vein Recognition ◽  
Finger Vein Recognition ◽  
Biometric Features

This work explores the field of biometric finger vein recognition – which is the identification of individuals using the unique vein patterns under their finger skins. This work also includes the implementation of an Android fingerprint biometric system using the Android Near InfraRed (NIR) module, which exists to show the similarities and differences between the two (fingervein and fingerprint) prevalent biometric features. This work thus confirms that finger vein recognition shows great promise as an accurate solution to modern society’s problem of automated personal authentication

scholarly journals Finger Vein Recognition Using Vgg-16 Cnn Algorithm

2020 ◽  
Vol 9 (8) ◽  
pp. 112-114
Keyword(s):  
Error Rate ◽  
Data Security ◽  
System Security ◽  
Biometric System ◽  
Electronic Technology ◽  
Equal Error Rate ◽  
Biometric Recognition ◽  
Finger Vein ◽  
Vein Recognition ◽  
Finger Vein Recognition

With the advancement in the electronic technology, data identification and security is to be mainly considered as a factor in the security. Biometric recognition has been taken in to consideration for security purpose. Data security has to be done to prevent the system security from transmission of data by unauthorized users. Various authentications are taken in to consideration but most commonly focuses on finger print biometric system. Biometric recognition is taken in priority which is high safe and security oriented. Preprocessing, extraction and Equal Error rate are taken in to consideration. In this we are mainly focusing in finger vein authentication domains over the system implementation.

Sign in / Sign up

Export Citation Format

Share Document