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

Call for Paper Volume 6 Issue 5 September-October 2024 Submit your research before last 3 days of October to publish your research paper in the issue of September-October.

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

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