Fingerprint recognition based on shark smell optimization and genetic algorithm

International Journal of Advances in Intelligent Informatics

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Field Value
 
Title Fingerprint recognition based on shark smell optimization and genetic algorithm
 
Creator Ahmed, Bakhan Tofiq
Abdulhameed, Omar Younis
 
Subject Fingerprint recognition; Swarm intelligence; Shark smell optimization; Genetic algorithm; Chebyshev polynomial first kind
 
Description Fingerprint recognition is a dominant form of biometric due to its distinctiveness. The study aims to extract and select the best features of fingerprint images, and evaluate the strength of the Shark Smell Optimization (SSO) and Genetic Algorithm (GA) in the search space with a chosen set of metrics. The proposed model consists of seven phases namely, enrollment, image preprocessing by using weighted median filter, feature extraction by using SSO, weight generation by using Chebyshev polynomial first kind (CPFK), feature selection by using GA, creation of a user’s database, and matching features by using Euclidean distance (ED). The effectiveness of the proposed model’s algorithms and performance is evaluated on 150 real fingerprint images that were collected from university students by the ZKTeco scanner at Sulaimani city, Iraq. The system’s performance was measured by three renowned error rate metrics, namely, False Acceptance Rate (FAR), False Rejection Rate (FRR), and Correct Verification Rate (CVR). The experimental outcome showed that the proposed fingerprint recognition model was exceedingly accurate recognition because of a low rate of both FAR and FRR, with a high CVR percentage gained which was 0.00, 0.00666, and 99.334%, respectively. This finding would be useful for improving biometric secure authentication based fingerprint. It is also possibly applied to other research topics such as fraud detection, e-payment, and other real-life applications authentication.
 
Publisher Universitas Ahmad Dahlan
 
Contributor
 
Date 2020-07-12
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion

 
Format application/pdf
 
Identifier http://ijain.org/index.php/IJAIN/article/view/502
10.26555/ijain.v6i2.502
 
Source International Journal of Advances in Intelligent Informatics; Vol 6, No 2 (2020): July 2020; 123-134
2548-3161
2442-6571
 
Language eng
 
Relation http://ijain.org/index.php/IJAIN/article/view/502/ijain_v6i2_p123-134
 
Rights https://creativecommons.org/licenses/by-sa/4.0
 

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