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Face Recognition using Independent Component Analysis Algorithm

by Zaid Abdi Alkareem Alyasseri
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 126 - Number 3
Year of Publication: 2015
Authors: Zaid Abdi Alkareem Alyasseri
10.5120/ijca2015906016

Zaid Abdi Alkareem Alyasseri . Face Recognition using Independent Component Analysis Algorithm. International Journal of Computer Applications. 126, 3 ( September 2015), 34-38. DOI=10.5120/ijca2015906016

@article{ 10.5120/ijca2015906016,
author = { Zaid Abdi Alkareem Alyasseri },
title = { Face Recognition using Independent Component Analysis Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { September 2015 },
volume = { 126 },
number = { 3 },
month = { September },
year = { 2015 },
issn = { 0975-8887 },
pages = { 34-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume126/number3/22534-2015906016/ },
doi = { 10.5120/ijca2015906016 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:16:30.577069+05:30
%A Zaid Abdi Alkareem Alyasseri
%T Face Recognition using Independent Component Analysis Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 126
%N 3
%P 34-38
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Face recognition system compares the tested face with the various training faces reserved in the database with an efficient success rate. The best matching of the tested face with the training faces is an important task. In this article, how to recognize a face is presented; two different analysis algorithms are included in the evaluation system: Eigenface and ICA. The local dataset used in this article is pre-processed using statistical standard methods. Pre-processing software, which is provided by the Colorado State University (CSU) Face Identification Evaluation System Version 5.0 under Unix Shell scripts, was written using ANSII C code. Independent Component Analysis algorithm (ICA) is written using Matlab for face recognition implementation. This article explains how the faces, having some variations such as facial expressions and viewing conditions w.r.t the original faces reserved in the database, are detected with an improved accuracy and success rate. Finally, the result shows several graphs by Matlab.

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Index Terms

Computer Science
Information Sciences

Keywords

Pattern Recognition Face Recognition System ICA algorithm Eigenface.

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