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Genetic Algorithm and Probabilistic Neural Networks for Fingerprint Identification

by Dhia Alzubaydi, Thikra Mohammed Abed
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 101 - Number 11
Year of Publication: 2014
Authors: Dhia Alzubaydi, Thikra Mohammed Abed
10.5120/17733-8846

Dhia Alzubaydi, Thikra Mohammed Abed . Genetic Algorithm and Probabilistic Neural Networks for Fingerprint Identification. International Journal of Computer Applications. 101, 11 ( September 2014), 34-39. DOI=10.5120/17733-8846

@article{ 10.5120/17733-8846,
author = { Dhia Alzubaydi, Thikra Mohammed Abed },
title = { Genetic Algorithm and Probabilistic Neural Networks for Fingerprint Identification },
journal = { International Journal of Computer Applications },
issue_date = { September 2014 },
volume = { 101 },
number = { 11 },
month = { September },
year = { 2014 },
issn = { 0975-8887 },
pages = { 34-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume101/number11/17733-8846/ },
doi = { 10.5120/17733-8846 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:31:25.014734+05:30
%A Dhia Alzubaydi
%A Thikra Mohammed Abed
%T Genetic Algorithm and Probabilistic Neural Networks for Fingerprint Identification
%J International Journal of Computer Applications
%@ 0975-8887
%V 101
%N 11
%P 34-39
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Existing security methods rely on knowledge based on approaches like password or token based on approaches like access cards. Such method is not very secure, biometrics such as fingerprint, face and voice offer means of personal identification and provide increased security because they rely on who we are. In this paper, algorithm fingerprint identification is introduced. The proposed algorithm has used 196 fingerprint image back to the twenty-eight individual 140 from them has been used for training and 56 image has been used for testing . Discrete Cosine Transform has been used to extract distinctive features from fingerprint image and genetic algorithm has been used as feature selection technique . Genetic algorithm has helped to produce GA filter in order to select subset of features out of DCT. When testing the proposed system by using Probabilistic Neural Network has found the identification rate reaching to 91%. This rate has emboldened on attempted using more one filter of genetic algorithm , the result that reached to 98% as identification rate with more reduction in number features.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Fingerprint Identification Fourier Transform Contrast Limited Adaptive Histogram Equalization Morphological Methods Poincare index Discrete Cosine Transform Genetic Algorithm Probabilistic Neural Network.