Face recognition system using principal component analysis and fuzzy artmap

Research on face recognition system has been conducted over the past thirty years. The common problem of face recognition systems is catastrophic forgetting where they need to retrain the whole data in order to add a new data. As a result, the training period, processing time, hidden layers and matr...

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Main Author:	Abdul Karim, Jamikaliza
Format:	Thesis
Language:	English
Published:	2009
Subjects:	QA75 Electronic computers Computer science
Online Access:	http://eprints.utm.my/id/eprint/18313/1/JamikalizaAbdulKarimMFKA2009.pdf
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id	my-utm-ep.18313
record_format	uketd_dc
spelling	my-utm-ep.183132018-06-25T09:01:48Z Face recognition system using principal component analysis and fuzzy artmap 2009-09 Abdul Karim, Jamikaliza QA75 Electronic computers. Computer science Research on face recognition system has been conducted over the past thirty years. The common problem of face recognition systems is catastrophic forgetting where they need to retrain the whole data in order to add a new data. As a result, the training period, processing time, hidden layers and matrix size of input network are increased. This research focused on solving the catastrophic forgetting problem and improving recognition rate. In this thesis, a face recognition system based on Fuzzy Artmap (FAM) as a classifier has been proposed. FAM is an incremental learning approach which offers a unique solution for stability-plasticity dilemma by preserving previously learned knowledge and adapting new patterns. Experiments were conducted to evaluate the performance of both FAM and Multilayer Perceptron Neural Network (MLPNN). The recognition rate obtained were 97.2% and 98.5% using FAM, 90.56% and 81.5% using MLPNN based on local and Olivetti Research Lab (ORL) datasets, respectively. Using FAM, the recognition rate improved by 6.64% and 17% for both datasets, respectively. The results proved that the proposed system offers a solution for catastrophic forgetting and improved recognition rate. 2009-09 Thesis http://eprints.utm.my/id/eprint/18313/ http://eprints.utm.my/id/eprint/18313/1/JamikalizaAbdulKarimMFKA2009.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QA75 Electronic computers Computer science
spellingShingle	QA75 Electronic computers Computer science Abdul Karim, Jamikaliza Face recognition system using principal component analysis and fuzzy artmap
description	Research on face recognition system has been conducted over the past thirty years. The common problem of face recognition systems is catastrophic forgetting where they need to retrain the whole data in order to add a new data. As a result, the training period, processing time, hidden layers and matrix size of input network are increased. This research focused on solving the catastrophic forgetting problem and improving recognition rate. In this thesis, a face recognition system based on Fuzzy Artmap (FAM) as a classifier has been proposed. FAM is an incremental learning approach which offers a unique solution for stability-plasticity dilemma by preserving previously learned knowledge and adapting new patterns. Experiments were conducted to evaluate the performance of both FAM and Multilayer Perceptron Neural Network (MLPNN). The recognition rate obtained were 97.2% and 98.5% using FAM, 90.56% and 81.5% using MLPNN based on local and Olivetti Research Lab (ORL) datasets, respectively. Using FAM, the recognition rate improved by 6.64% and 17% for both datasets, respectively. The results proved that the proposed system offers a solution for catastrophic forgetting and improved recognition rate.
format	Thesis
qualification_level	Master's degree
author	Abdul Karim, Jamikaliza
author_facet	Abdul Karim, Jamikaliza
author_sort	Abdul Karim, Jamikaliza
title	Face recognition system using principal component analysis and fuzzy artmap
title_short	Face recognition system using principal component analysis and fuzzy artmap
title_full	Face recognition system using principal component analysis and fuzzy artmap
title_fullStr	Face recognition system using principal component analysis and fuzzy artmap
title_full_unstemmed	Face recognition system using principal component analysis and fuzzy artmap
title_sort	face recognition system using principal component analysis and fuzzy artmap
granting_institution	Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department	Faculty of Electrical Engineering
publishDate	2009
url	http://eprints.utm.my/id/eprint/18313/1/JamikalizaAbdulKarimMFKA2009.pdf
_version_	1747815244493750272

Face recognition system using principal component analysis and fuzzy artmap

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