Texture classification and discrimination for region-based image retrieval
In RBIR, texture features are crucial in determining the class a region belongs to since they can overcome the limitations of color and shape features. Two robust approaches to model texture features are Gabor and curvelet features. Although both features are close to human visual perception, suffic...
| Main Authors: | , , , |
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| Format: | Article |
| Published: |
Elsevier
2015
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| Online Access: | http://psasir.upm.edu.my/id/eprint/35620/ |
| _version_ | 1848848105929179136 |
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| author | Zand, Mohsen Doraisamy, Shyamala Abdul Halin, Alfian Mustaffa, Mas Rina |
| author_facet | Zand, Mohsen Doraisamy, Shyamala Abdul Halin, Alfian Mustaffa, Mas Rina |
| author_sort | Zand, Mohsen |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | In RBIR, texture features are crucial in determining the class a region belongs to since they can overcome the limitations of color and shape features. Two robust approaches to model texture features are Gabor and curvelet features. Although both features are close to human visual perception, sufficient information needs to be extracted from their sub-bands for effective texture classification. Moreover, shape irregularity can be a problem since Gabor and curvelet transforms can only be applied on the regular shapes. In this paper, we propose an approach that uses both the Gabor wavelet and the curvelet transforms on the transferred regular shapes of the image regions. We also apply a fitting method to encode the sub-bands’ information in the polynomial coefficients to create a texture feature vector with the maximum power of discrimination. Experiments on texture classification task with ImageCLEF and Outex databases demonstrate the effectiveness of the proposed approach. |
| first_indexed | 2025-11-15T09:29:13Z |
| format | Article |
| id | upm-35620 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T09:29:13Z |
| publishDate | 2015 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-356202016-01-18T02:53:52Z http://psasir.upm.edu.my/id/eprint/35620/ Texture classification and discrimination for region-based image retrieval Zand, Mohsen Doraisamy, Shyamala Abdul Halin, Alfian Mustaffa, Mas Rina In RBIR, texture features are crucial in determining the class a region belongs to since they can overcome the limitations of color and shape features. Two robust approaches to model texture features are Gabor and curvelet features. Although both features are close to human visual perception, sufficient information needs to be extracted from their sub-bands for effective texture classification. Moreover, shape irregularity can be a problem since Gabor and curvelet transforms can only be applied on the regular shapes. In this paper, we propose an approach that uses both the Gabor wavelet and the curvelet transforms on the transferred regular shapes of the image regions. We also apply a fitting method to encode the sub-bands’ information in the polynomial coefficients to create a texture feature vector with the maximum power of discrimination. Experiments on texture classification task with ImageCLEF and Outex databases demonstrate the effectiveness of the proposed approach. Elsevier 2015-01 Article PeerReviewed Zand, Mohsen and Doraisamy, Shyamala and Abdul Halin, Alfian and Mustaffa, Mas Rina (2015) Texture classification and discrimination for region-based image retrieval. Journal of Visual Communication and Image Representation, 26. pp. 305-316. ISSN 1047-3203; ESSN: 1095-9076 http://www.sciencedirect.com/science/article/pii/S1047320314001643 10.1016/j.jvcir.2014.10.005 |
| spellingShingle | Zand, Mohsen Doraisamy, Shyamala Abdul Halin, Alfian Mustaffa, Mas Rina Texture classification and discrimination for region-based image retrieval |
| title | Texture classification and discrimination for region-based image retrieval |
| title_full | Texture classification and discrimination for region-based image retrieval |
| title_fullStr | Texture classification and discrimination for region-based image retrieval |
| title_full_unstemmed | Texture classification and discrimination for region-based image retrieval |
| title_short | Texture classification and discrimination for region-based image retrieval |
| title_sort | texture classification and discrimination for region-based image retrieval |
| url | http://psasir.upm.edu.my/id/eprint/35620/ http://psasir.upm.edu.my/id/eprint/35620/ http://psasir.upm.edu.my/id/eprint/35620/ |