IKP Based Biometric Authentication Using Artificial Neural Network

Viswanathan, M and Babu Loganathan, Ganesh and Srinivasan, S (2020) IKP Based Biometric Authentication Using Artificial Neural Network. AIP Conference Proceedings, 2271 (1).

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Abstract

The primary objective of this paper is to verify individuals as indicated by their finger surfaces. We propose to remove Finger Texture (FT) highlights of the two finger pictures (center, ring) from a low goal contactless hand picture utilizing LBP strategy. The utilization of Inner-Knuckle-Print (IKP) in biometric recognition is the most broadly proposed validation work. The unique characteristics of the IKP give us the requirement for recognizable proof. During the IKP filtering process, the image created by the scanner might be partially unique. This paper proposes artificial neural networks for effectively coordinating procedures to IKP validation. By utilizing the Back-Propagation method, the algorithm coordinates IKP and relates them to a novel accomplished client. After grouping, the procedure restores to the best counterpart for the given finger impression variables.

Item Type: Article
Uncontrolled Keywords: Pre-Processing, Feature extraction, LBP, Classification, ANN.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Depositing User: ePrints deposit
Date Deposited: 08 Mar 2021 07:28
Last Modified: 01 Nov 2021 07:47
URI: http://eprints.tiu.edu.iq/id/eprint/415

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