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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Praise Worthy Prize
2014
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| Online Access: | http://psasir.upm.edu.my/id/eprint/36537/ http://psasir.upm.edu.my/id/eprint/36537/1/Artificial%20neural%20network.pdf |
| _version_ | 1848848360366145536 |
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| author | Ashour, Mohammed W. Khalid, Fatimah Abdullah, Lili Nurliyana Abdul Halin, Alfian |
| author_facet | Ashour, Mohammed W. Khalid, Fatimah Abdullah, Lili Nurliyana Abdul Halin, Alfian |
| author_sort | Ashour, Mohammed W. |
| building | UPM Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T09:33:16Z |
| format | Article |
| id | upm-36537 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T09:33:16Z |
| publishDate | 2014 |
| publisher | Praise Worthy Prize |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-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 |
| spellingShingle | Ashour, Mohammed W. Khalid, Fatimah Abdullah, Lili Nurliyana Abdul Halin, Alfian Artificial neural network-based texture classification using reduced multidirectional Gabor features |
| title | 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_short | Artificial neural network-based texture classification using reduced multidirectional Gabor features |
| title_sort | artificial neural network-based texture classification using reduced multidirectional gabor features |
| url | http://psasir.upm.edu.my/id/eprint/36537/ http://psasir.upm.edu.my/id/eprint/36537/1/Artificial%20neural%20network.pdf |