Analysis of Finger Vein Feature Extraction and Recognition using DA and KNN Methods
Ruqaiya Khanam, Ramsha Khan, Rajeev Ranjan · 2019
A steady growth in terms of development alongwith the use of consumer electronics has been noticed which is a consequence of and increased rate of globalization that has raised the living standards. This has arisen a need for high security authentication systems in order to safeguard personal information stored on mobile devices. Since the high complexity and security of existing biometric systems is becoming the prime concern in terms of space and time, automated personal identification using finger-vein biometric is emerging to be a prominent topic in both practical as well as examination applications. In this paper, using MATLAB 2016a, we present discriminant analysis and KNN of machine learning method, as it stands for K- nearest neighbor algorithm are used to verify and calculate the accuracy of the features of the finger vein images. Thus, the accuracy obtained from KNN is 55.84% whereas from discriminant analysis the accuracy obtained is 92.21%. Finally discriminant analysis is more accurate than KNN technique.