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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主要作者: Abdul Karim, Jamikaliza
格式: Thesis
语言:English
出版: 2009
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在线阅读:http://eprints.utm.my/id/eprint/18313/1/JamikalizaAbdulKarimMFKA2009.pdf
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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