Features extraction of fingerprints based on hybrid particle swarm optimization and bat algorithms

Authors

DOI:

https://doi.org/10.15587/1729-4061.2022.266259

Keywords:

image processing, biometrics, fingerprint, features extraction, minutiae, binarization, thinning, swarm intelligence, particle swarm optimization, bat algorithm

Abstract

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 swarm-based 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

Author Biographies

Ahmed Luay Ahmed, Supervision and Scientific Apparatus, Ministry of Higher Education and Scientific Research

Lecturer, Master of Computer Sciences

Department of Accreditation

Noor Hasan Hassoon, University of Diyala

Lucturer, Master of Computer Sciences

Department of Computer

College of Education for Pure Science

Layla AL.hak, University of Diyala

Lecturer, Master of Computer Sciences

Department of Computer

College of Science

Mahdi Edan, AL-Rasheed University College

Doctor of Applied Physics

Department ofw Computer Techniques Engineering

Hazim Noman Abed, University of Diyala

Assistant Professor, Master of Computer Sciences

Department of Computer

College of Science

Sura Khalil Abd, Dijlah University College, Universiti Tenaga Nasional

Doctor of Network and Communication Systems Engineering

Department of Computer Techniques Engineering

Department of Computer Science and Information Technology

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Features extraction of fingerprints based on hybrid particle swarm optimization and bat algorithms

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Published

2022-10-30

How to Cite

Luay Ahmed, A., Hassoon, N. H., AL.hak, L., Edan, M., Abed, H. N., & Abd, S. K. (2022). Features extraction of fingerprints based on hybrid particle swarm optimization and bat algorithms. Eastern-European Journal of Enterprise Technologies, 5(2(119), 55–61. https://doi.org/10.15587/1729-4061.2022.266259

Issue

Vol. 5 No. 2(119) (2022): Information technology. Industry control systems

Section

Information technology

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Copyright (c) 2022 Ahmed LuayAhmed, Noor Hassoon, Layla AL.hak, Mahdi Edan, Hazim Abed, Sura Abd

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