IKP based biometric authentication using artificial neural network

M., Viswanathan and Babu Loganathan, Ganesh and S., Srinivasan (2020) IKP based biometric authentication using artificial neural network. AIP Conference Proceedings, 2271 (1). pp. 1-8.

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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: Engineering > Computer engineering
Depositing User: ePrints deposit
Date Deposited: 07 Apr 2021 08:56
Last Modified: 05 Dec 2022 07:48
URI: http://eprints.tiu.edu.iq/id/eprint/505

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