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Image Processing Using Principal Component Analysis

by Pramod Kumar Pandey, Yaduvir Singh, Sweta Tripathi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 15 - Number 4
Year of Publication: 2011
Authors: Pramod Kumar Pandey, Yaduvir Singh, Sweta Tripathi
10.5120/1935-2582

Pramod Kumar Pandey, Yaduvir Singh, Sweta Tripathi . Image Processing Using Principal Component Analysis. International Journal of Computer Applications. 15, 4 ( February 2011), 37-40. DOI=10.5120/1935-2582

@article{ 10.5120/1935-2582,
author = { Pramod Kumar Pandey, Yaduvir Singh, Sweta Tripathi },
title = { Image Processing Using Principal Component Analysis },
journal = { International Journal of Computer Applications },
issue_date = { February 2011 },
volume = { 15 },
number = { 4 },
month = { February },
year = { 2011 },
issn = { 0975-8887 },
pages = { 37-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume15/number4/1935-2582/ },
doi = { 10.5120/1935-2582 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:03:17.493602+05:30
%A Pramod Kumar Pandey
%A Yaduvir Singh
%A Sweta Tripathi
%T Image Processing Using Principal Component Analysis
%J International Journal of Computer Applications
%@ 0975-8887
%V 15
%N 4
%P 37-40
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, a review on the latest methodologies and application of the Principle Component Analysis (PCA) has been done in the area of image processing. Exploring basic theory of multivariate analysis, which involves a mathematical procedure to transform a number of correlated variables into a number of uncorrelated variables have been studied, compared and analyzed for better performance. The PCA ultimately reduces the number of effective variables used for classification which are compared with some statistical method. A comparison is made to illustrate the important of PCA in various signal processing based application like Texture classification, Face recognition, Biometrics etc.

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Index Terms

Computer Science
Information Sciences

Keywords

Image Processing Component Analysis

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