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...

Full description

Bibliographic Details
Main Author: Abdul Karim, Jamikaliza
Format: Thesis
Language:English
Published: 2009
Subjects:
Online Access:http://eprints.utm.my/18313/1/JamikalizaAbdulKarimMFKA2009.pdf
_version_ 1796855682920611840
author Abdul Karim, Jamikaliza
author_facet Abdul Karim, Jamikaliza
author_sort Abdul Karim, Jamikaliza
collection ePrints
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.
first_indexed 2024-03-05T18:32:10Z
format Thesis
id utm.eprints-18313
institution Universiti Teknologi Malaysia - ePrints
language English
last_indexed 2024-03-05T18:32:10Z
publishDate 2009
record_format dspace
spelling utm.eprints-183132018-06-25T09:01:48Z http://eprints.utm.my/18313/ Face recognition system using principal component analysis and fuzzy artmap 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 NonPeerReviewed application/pdf en http://eprints.utm.my/18313/1/JamikalizaAbdulKarimMFKA2009.pdf Abdul Karim, Jamikaliza (2009) Face recognition system using principal component analysis and fuzzy artmap. Masters thesis, Universiti Teknologi Malaysia, Faculty of Electrical Engineering.
spellingShingle QA75 Electronic computers. Computer science
Abdul Karim, Jamikaliza
Face recognition system using principal component analysis and fuzzy artmap
title 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_short Face recognition system using principal component analysis and fuzzy artmap
title_sort face recognition system using principal component analysis and fuzzy artmap
topic QA75 Electronic computers. Computer science
url http://eprints.utm.my/18313/1/JamikalizaAbdulKarimMFKA2009.pdf
work_keys_str_mv AT abdulkarimjamikaliza facerecognitionsystemusingprincipalcomponentanalysisandfuzzyartmap