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Artificial neural network-based texture classification using reduced multidirectional Gabor features

In this paper, a technique to classify Engineering Machined Textures (EMT) into the six classes of Turning, Grinding, Horizontal-Milling, Vertical-Milling, Lapping and Shaping, is presented. Multidirectional Gabor features are firstly extracted from each image followed by a dimensionality reduction...

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Main Authors: Ashour, Mohammed W., Khalid, Fatimah, Abdullah, Lili Nurliyana, Abdul Halin, Alfian
Format: Article
Language:English
Published: Praise Worthy Prize 2014
Online Access:http://psasir.upm.edu.my/id/eprint/36537/1/Artificial%20neural%20network.pdf
http://psasir.upm.edu.my/id/eprint/36537/
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spelling my.upm.eprints.365372015-08-24T02:53:10Z http://psasir.upm.edu.my/id/eprint/36537/ Artificial neural network-based texture classification using reduced multidirectional Gabor features Ashour, Mohammed W. Khalid, Fatimah Abdullah, Lili Nurliyana Abdul Halin, Alfian In this paper, a technique to classify Engineering Machined Textures (EMT) into the six classes of Turning, Grinding, Horizontal-Milling, Vertical-Milling, Lapping and Shaping, is presented. Multidirectional Gabor features are firstly extracted from each image followed by a dimensionality reduction step using Principal Components Analysis (PCA). The images are finally classified using a supervised Artificial Neural Network (ANN) classifier. Experimental results using a 72-image dataset demonstrate that PCA is able to reduce computational time while improving classification accuracy. In addition, the use of the proposed Gabor filter seems to be more robust compared to other existing techniques. Praise Worthy Prize 2014-06 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/36537/1/Artificial%20neural%20network.pdf Ashour, Mohammed W. and Khalid, Fatimah and Abdullah, Lili Nurliyana and Abdul Halin, Alfian (2014) Artificial neural network-based texture classification using reduced multidirectional Gabor features. International Review on Computers and Software, 9 (6). pp. 1007-1016. ISSN 1828-6003; ESSN: 1828-6011
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description In this paper, a technique to classify Engineering Machined Textures (EMT) into the six classes of Turning, Grinding, Horizontal-Milling, Vertical-Milling, Lapping and Shaping, is presented. Multidirectional Gabor features are firstly extracted from each image followed by a dimensionality reduction step using Principal Components Analysis (PCA). The images are finally classified using a supervised Artificial Neural Network (ANN) classifier. Experimental results using a 72-image dataset demonstrate that PCA is able to reduce computational time while improving classification accuracy. In addition, the use of the proposed Gabor filter seems to be more robust compared to other existing techniques.
format Article
author Ashour, Mohammed W.
Khalid, Fatimah
Abdullah, Lili Nurliyana
Abdul Halin, Alfian
spellingShingle Ashour, Mohammed W.
Khalid, Fatimah
Abdullah, Lili Nurliyana
Abdul Halin, Alfian
Artificial neural network-based texture classification using reduced multidirectional Gabor features
author_facet Ashour, Mohammed W.
Khalid, Fatimah
Abdullah, Lili Nurliyana
Abdul Halin, Alfian
author_sort Ashour, Mohammed W.
title Artificial neural network-based texture classification using reduced multidirectional Gabor features
title_short Artificial neural network-based texture classification using reduced multidirectional Gabor features
title_full Artificial neural network-based texture classification using reduced multidirectional Gabor features
title_fullStr Artificial neural network-based texture classification using reduced multidirectional Gabor features
title_full_unstemmed Artificial neural network-based texture classification using reduced multidirectional Gabor features
title_sort artificial neural network-based texture classification using reduced multidirectional gabor features
publisher Praise Worthy Prize
publishDate 2014
url http://psasir.upm.edu.my/id/eprint/36537/1/Artificial%20neural%20network.pdf
http://psasir.upm.edu.my/id/eprint/36537/
_version_ 1643831766471933952
score 13.211869

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