Research Article
A Comparison between PCA and SIFT Algorithms in Face Recognition Accuracy
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International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
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| Volume 12 - Issue 39 |
| Published: October 2022 |
| Authors: Israa Abdulrauof Othman, Sallam Osman Fageeri, Ashraf Osman Ibrahim |
10.5120/ijais2022451934
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Israa Abdulrauof Othman, Sallam Osman Fageeri, Ashraf Osman Ibrahim . A Comparison between PCA and SIFT Algorithms in Face Recognition Accuracy. International Journal of Applied Information Systems. 12, 39 (October 2022), 52-55. DOI=10.5120/ijais2022451934
@article{ 10.5120/ijais2022451934,
author = { Israa Abdulrauof Othman,Sallam Osman Fageeri,Ashraf Osman Ibrahim },
title = { A Comparison between PCA and SIFT Algorithms in Face Recognition Accuracy },
journal = { International Journal of Applied Information Systems },
year = { 2022 },
volume = { 12 },
number = { 39 },
pages = { 52-55 },
doi = { 10.5120/ijais2022451934 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2022
%A Israa Abdulrauof Othman
%A Sallam Osman Fageeri
%A Ashraf Osman Ibrahim
%T A Comparison between PCA and SIFT Algorithms in Face Recognition Accuracy%T
%J International Journal of Applied Information Systems
%V 12
%N 39
%P 52-55
%R 10.5120/ijais2022451934
%I Foundation of Computer Science (FCS), NY, USA
Abstract
The systems that use facial recognition have contributed to the identification of criminals or wanted persons or even to control attendance and departure. However, the problem is whether the error rate is large. This may cause many problems. There are many useful aid such as SIFT and PCA. The purpose of this research is to analyze and compare the performance i.e. accuracy of principles of Comparison Analysis (PCA) and (SIFT) algorithms. The evaluation method used is a confusion matrix for measuring accuracy in precision, recall, F-measure, and success rate. Based on the comparative analysis, the (SIFT) algorithm gains the accuracy better by variation of compared to (PCA) algorithm in the implementation for 5 research data sets.
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