International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
•
Impact Factor: 9.24
A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
Home
Research Paper
Submit Research Paper
Publication Guidelines
Publication Charges
Upload Documents
Track Status / Pay Fees / Download Publication Certi.
Editors & Reviewers
View All
Join as a Reviewer
Reviewer Referral Program
Get Membership Certificate
Current Issue
Publication Archive
Conference
Publishing Conf. with IJFMR
Upcoming Conference(s) ↓
WSMCDD-2025
GSMCDD-2025
Conferences Published ↓
RBS:RH-COVID-19 (2023)
ICMRS'23
PIPRDA-2023
Contact Us
Plagiarism is checked by the leading plagiarism checker
Call for Paper
Volume 6 Issue 6
November-December 2024
Indexing Partners
Deep Learning-Based Biometric Finger Vein Authentication System for Enhanced Security
Author(s) | Padmapriya P, J. Saminathan, I. Lakshmi Priya, M.Dayanidhy |
---|---|
Country | India |
Abstract | Biometrics, which uses human physiological characteristics, is a method for protecting personal information. Recently, finger vein authentication has become one of the most popular biometric techniques. This method offers high security and accuracy, making it a reliable form of biometric authentication. The system compares a person's vascular structure in their finger to previously collected data. Finger vein authentication works by identifying vein patterns beneath the skin's surface. The proposed system aims to enhance user authentication security by leveraging the uniqueness of finger vein patterns. The finger vein image is obtained from a database, and preprocessing is done using a Gaussian median filter in both spatial and frequency domains to remove noise. Image segmentation is performed through a line tracking method, which enhances image contrast. For feature extraction, the system utilizes Convolutional Neural Networks (CNN), and these features are matched with the stored finger vein database. A deep learning approach is then applied to classify users as genuine or imposters. In real-time, a scanner captures the finger vein image, which is sent to an Arduino board for storage and subsequently processed in MATLAB for classification. The result is transmitted through a GSM module as an alert or message, and the information is also stored in an IoT system for future reference. A GSM module is integrated with the user for communication. The proposed system achieves an accuracy of 96%, making it highly beneficial for security applications like access control, identity verification, banking, and financial transactions. |
Keywords | Biometric Recognition, Finger Vein, Line Tracking, Convolution neural network, Gaussian Filter |
Field | Engineering |
Published In | Volume 6, Issue 5, September-October 2024 |
Published On | 2024-09-22 |
Cite This | Deep Learning-Based Biometric Finger Vein Authentication System for Enhanced Security - Padmapriya P, J. Saminathan, I. Lakshmi Priya, M.Dayanidhy - IJFMR Volume 6, Issue 5, September-October 2024. DOI 10.36948/ijfmr.2024.v06i05.27652 |
DOI | https://doi.org/10.36948/ijfmr.2024.v06i05.27652 |
Short DOI | https://doi.org/g4qmpj |
Share this
E-ISSN 2582-2160
doi
CrossRef DOI is assigned to each research paper published in our journal.
IJFMR DOI prefix is
10.36948/ijfmr
Downloads
All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.