FEATURES EXTRACTION OF FINGERPRINTS BASED ON HYBRID PARTICLE SWARM OPTIMIZATION AND BAT ALGORITHMS
Most security system's essential errand is to check that the people are in fact who they claim to be. In Contrast to traditional techniques such as passwords and smart cards that are used in some organizations, fingerprint identification may be preferred as it makes the information virtually im...
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my.uniten.dspace-270752023-05-29T17:39:19Z FEATURES EXTRACTION OF FINGERPRINTS BASED ON HYBRID PARTICLE SWARM OPTIMIZATION AND BAT ALGORITHMS Ahmed A.L. Hassoon N. Hak L.A.L. Edan M. Abed H. Abd S. 57223270561 57204876049 57215288053 57224221770 56394288600 56516784600 Most security system's essential errand is to check that the people are in fact who they claim to be. In Contrast to traditional techniques such as passwords and smart cards that are used in some organizations, fingerprint identification may be preferred as it makes the information virtually impossible to steal. The most extensive used biometric features are Fingerprints, in order to identify a person because of their uniqueness and invariance. The fingerprint consists of valleys and ridges on the surface of a fingertip. In this paper, a new hybrid strategy Particle Swarm Optimization (PSO) with Bat Algorithm (BA) is proposed to extract features from fingerprint images. Both PSO and BA algorithms are swarmbased algorithms that mimics the swarm behaviour of particles and bats in nature. In the field of image processing, features are extremely significant. Before obtaining features, the noisy area should be removed from the foreground first, and then several important techniques are applied on each sample image in the database such as Fingerprint Enhancement by using Fast Fourier Transform (FFT), Binarization, and Thinning. The hybrid (PSO-BA) algorithm is proposed as a pre-enhancing step to select the clear minutiae (or feature) structures across several iterations, which will be more suited for the matching phase. By comparing the proposed method with several methods in calculating FAR and FRR, the results showed that the FAR (0.001) and FRR (0.01) were less than the other proposed methods. That means the hybrid (PSO-BA) algorithm has the better results, which means it can be used as one of the best search approaches to extract features from fingerprints � 2022, Authors. This is an open access article under the Creative Commons CC BY license Final 2023-05-29T09:39:19Z 2023-05-29T09:39:19Z 2022 Article 10.15587/1729-4061.2022.266259 2-s2.0-85141762457 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141762457&doi=10.15587%2f1729-4061.2022.266259&partnerID=40&md5=08c29a3f92241c1ae0ba775ea03986a4 https://irepository.uniten.edu.my/handle/123456789/27075 5 2-119 55 61 All Open Access, Gold, Green Technology Center Scopus |
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Most security system's essential errand is to check that the people are in fact who they claim to be. In Contrast to traditional techniques such as passwords and smart cards that are used in some organizations, fingerprint identification may be preferred as it makes the information virtually impossible to steal. The most extensive used biometric features are Fingerprints, in order to identify a person because of their uniqueness and invariance. The fingerprint consists of valleys and ridges on the surface of a fingertip. In this paper, a new hybrid strategy Particle Swarm Optimization (PSO) with Bat Algorithm (BA) is proposed to extract features from fingerprint images. Both PSO and BA algorithms are swarmbased algorithms that mimics the swarm behaviour of particles and bats in nature. In the field of image processing, features are extremely significant. Before obtaining features, the noisy area should be removed from the foreground first, and then several important techniques are applied on each sample image in the database such as Fingerprint Enhancement by using Fast Fourier Transform (FFT), Binarization, and Thinning. The hybrid (PSO-BA) algorithm is proposed as a pre-enhancing step to select the clear minutiae (or feature) structures across several iterations, which will be more suited for the matching phase. By comparing the proposed method with several methods in calculating FAR and FRR, the results showed that the FAR (0.001) and FRR (0.01) were less than the other proposed methods. That means the hybrid (PSO-BA) algorithm has the better results, which means it can be used as one of the best search approaches to extract features from fingerprints � 2022, Authors. This is an open access article under the Creative Commons CC BY license |
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57223270561 |
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57223270561 Ahmed A.L. Hassoon N. Hak L.A.L. Edan M. Abed H. Abd S. |
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Ahmed A.L. Hassoon N. Hak L.A.L. Edan M. Abed H. Abd S. |
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Ahmed A.L. Hassoon N. Hak L.A.L. Edan M. Abed H. Abd S. FEATURES EXTRACTION OF FINGERPRINTS BASED ON HYBRID PARTICLE SWARM OPTIMIZATION AND BAT ALGORITHMS |
author_sort |
Ahmed A.L. |
title |
FEATURES EXTRACTION OF FINGERPRINTS BASED ON HYBRID PARTICLE SWARM OPTIMIZATION AND BAT ALGORITHMS |
title_short |
FEATURES EXTRACTION OF FINGERPRINTS BASED ON HYBRID PARTICLE SWARM OPTIMIZATION AND BAT ALGORITHMS |
title_full |
FEATURES EXTRACTION OF FINGERPRINTS BASED ON HYBRID PARTICLE SWARM OPTIMIZATION AND BAT ALGORITHMS |
title_fullStr |
FEATURES EXTRACTION OF FINGERPRINTS BASED ON HYBRID PARTICLE SWARM OPTIMIZATION AND BAT ALGORITHMS |
title_full_unstemmed |
FEATURES EXTRACTION OF FINGERPRINTS BASED ON HYBRID PARTICLE SWARM OPTIMIZATION AND BAT ALGORITHMS |
title_sort |
features extraction of fingerprints based on hybrid particle swarm optimization and bat algorithms |
publisher |
Technology Center |
publishDate |
2023 |
_version_ |
1806426398164779008 |
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13.18916 |