Face Recognition Using MLP and RBF Neural Network with Gabor and Discrete Wavelet Transform Characterization: A Comparative Study
Face recognition has received a great attention from a lot of researchers in computer vision, pattern recognition, and human machine computer interfaces in recent years. Designing a face recognition system is a complex task due to the wide variety of illumination, pose, and facial expression. A lot...
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2015/523603 |
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doaj-ac18c94ba2bb421598dc1ede678a01e22020-11-24T22:58:10ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472015-01-01201510.1155/2015/523603523603Face Recognition Using MLP and RBF Neural Network with Gabor and Discrete Wavelet Transform Characterization: A Comparative StudyFatma Zohra Chelali0Amar Djeradi1Speech Communication and Signal Processing Laboratory, Faculty of Electronics and Computer Science, University of Science and Technology Houari Boumedienne (USTHB), P.O. Box 32, 16111 Algiers, AlgeriaSpeech Communication and Signal Processing Laboratory, Faculty of Electronics and Computer Science, University of Science and Technology Houari Boumedienne (USTHB), P.O. Box 32, 16111 Algiers, AlgeriaFace recognition has received a great attention from a lot of researchers in computer vision, pattern recognition, and human machine computer interfaces in recent years. Designing a face recognition system is a complex task due to the wide variety of illumination, pose, and facial expression. A lot of approaches have been developed to find the optimal space in which face feature descriptors are well distinguished and separated. Face representation using Gabor features and discrete wavelet has attracted considerable attention in computer vision and image processing. We describe in this paper a face recognition system using artificial neural networks like multilayer perceptron (MLP) and radial basis function (RBF) where Gabor and discrete wavelet based feature extraction methods are proposed for the extraction of features from facial images using two facial databases: the ORL and computer vision. Good recognition rate was obtained using Gabor and DWT parameterization with MLP classifier applied for computer vision dataset.http://dx.doi.org/10.1155/2015/523603 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Fatma Zohra Chelali Amar Djeradi |
spellingShingle |
Fatma Zohra Chelali Amar Djeradi Face Recognition Using MLP and RBF Neural Network with Gabor and Discrete Wavelet Transform Characterization: A Comparative Study Mathematical Problems in Engineering |
author_facet |
Fatma Zohra Chelali Amar Djeradi |
author_sort |
Fatma Zohra Chelali |
title |
Face Recognition Using MLP and RBF Neural Network with Gabor and Discrete Wavelet Transform Characterization:
A Comparative Study |
title_short |
Face Recognition Using MLP and RBF Neural Network with Gabor and Discrete Wavelet Transform Characterization:
A Comparative Study |
title_full |
Face Recognition Using MLP and RBF Neural Network with Gabor and Discrete Wavelet Transform Characterization:
A Comparative Study |
title_fullStr |
Face Recognition Using MLP and RBF Neural Network with Gabor and Discrete Wavelet Transform Characterization:
A Comparative Study |
title_full_unstemmed |
Face Recognition Using MLP and RBF Neural Network with Gabor and Discrete Wavelet Transform Characterization:
A Comparative Study |
title_sort |
face recognition using mlp and rbf neural network with gabor and discrete wavelet transform characterization:
a comparative study |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2015-01-01 |
description |
Face recognition has received a great attention from a lot of researchers in computer vision, pattern recognition, and human machine computer interfaces in recent years. Designing a face recognition system is a complex task due to the wide variety of illumination, pose, and facial expression. A lot of approaches have been developed to find the optimal space in which face feature descriptors are well distinguished and separated. Face representation using Gabor features and discrete wavelet has attracted considerable attention in computer vision and image processing. We describe in this paper a face recognition system using artificial neural networks like multilayer perceptron (MLP) and radial basis function (RBF) where Gabor and discrete wavelet based feature extraction methods are proposed for the extraction of features from facial images using two facial databases: the ORL and computer vision. Good recognition rate was obtained using Gabor and DWT parameterization with MLP classifier applied for computer vision dataset. |
url |
http://dx.doi.org/10.1155/2015/523603 |
work_keys_str_mv |
AT fatmazohrachelali facerecognitionusingmlpandrbfneuralnetworkwithgaboranddiscretewavelettransformcharacterizationacomparativestudy AT amardjeradi facerecognitionusingmlpandrbfneuralnetworkwithgaboranddiscretewavelettransformcharacterizationacomparativestudy |
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