Principle component analysis based face recognition

Face recognition is a process that takes a person’s query image and compares it with the images in the database that has been registered. This method is considered as one of the biometric technologies that have become widespread. It is a set of potential applications such as information security, ba...

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Main Authors: Breesam, Aqeel M., Wail, Mousa K., Fayadh, Rashid A.
Format: Conference Proceeding
Language:English
Subjects:
Covariance matrix
Face recognition
Object recognition
Principal components analysis
Reduction
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Wail, Mousa K.
Fayadh, Rashid A.
description Face recognition is a process that takes a person’s query image and compares it with the images in the database that has been registered. This method is considered as one of the biometric technologies that have become widespread. It is a set of potential applications such as information security, banking services and human interaction with the computer. This paper proposes building a face recognition system using principal component analysis and depends on retrieving the database. To measure the performance of the principal component analysis method, some tests were done with ‘faces94’ database that consist of 15 individuals (6 males and 9 females) with total 450 images as 30 images for each one. To reduce a number of variables, a statistical approach based on feature reduction is used based on covariance matrix to get dimensional reduction. The results were obtained using Matlab programming.
doi_str_mv 10.1063/5.0093821
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source American Institute of Physics:Jisc Collections:Transitional Journals Agreement 2021-23 (Reading list)
subjects Covariance matrix
Face recognition
Object recognition
Principal components analysis
Reduction
title Principle component analysis based face recognition
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