Content-based image retrieval using colour and shape fused features
Multi-feature methods are able to contribute to a more effective method compared to single-feature methods since feature fusion methods will be able to close the gap that exists in the single-feature methods. This paper presents a feature fusion method, which focuses on extracting colour and shape f...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Universiti Putra Malaysia Press
2013
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/40505/ http://psasir.upm.edu.my/id/eprint/40505/1/32.%20Content-based%20Image%20Retrieval%20Using%20Colour%20and%20Shape%20Fused.pdf |
| _version_ | 1848849445565759488 |
|---|---|
| author | Mustaffa, Mas Rina Ahmad, Fatimah Mahmod, Ramlan Doraisamy, Shyamala |
| author_facet | Mustaffa, Mas Rina Ahmad, Fatimah Mahmod, Ramlan Doraisamy, Shyamala |
| author_sort | Mustaffa, Mas Rina |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Multi-feature methods are able to contribute to a more effective method compared to single-feature methods since feature fusion methods will be able to close the gap that exists in the single-feature methods. This paper presents a feature fusion method, which focuses on extracting colour and shape features for content-based image retrieval (CBIR). The colour feature is extracted based on the proposed Multi-resolution Joint Auto Correlograms (MJAC), while the shape information is obtained through the proposed Extended Generalised Ridgelet-Fourier (EGRF). These features are fused together through a proposed integrated scheme. The feature fusion method has been tested on the SIMPLIcity image database, where several retrieval measurements are utilised to compare the effectiveness of the proposed method with few other comparable methods. The retrieval results show that the proposed Integrated Colour-shape (ICS) descriptor has successfully obtained the best overall retrieval performance in all the retrieval measurements as compared to the benchmark methods, which include precision (53.50%), precision at 11 standard recall levels (52.48%), and rank (17.40). |
| first_indexed | 2025-11-15T09:50:31Z |
| format | Article |
| id | upm-40505 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T09:50:31Z |
| publishDate | 2013 |
| publisher | Universiti Putra Malaysia Press |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-405052015-11-04T07:34:24Z http://psasir.upm.edu.my/id/eprint/40505/ Content-based image retrieval using colour and shape fused features Mustaffa, Mas Rina Ahmad, Fatimah Mahmod, Ramlan Doraisamy, Shyamala Multi-feature methods are able to contribute to a more effective method compared to single-feature methods since feature fusion methods will be able to close the gap that exists in the single-feature methods. This paper presents a feature fusion method, which focuses on extracting colour and shape features for content-based image retrieval (CBIR). The colour feature is extracted based on the proposed Multi-resolution Joint Auto Correlograms (MJAC), while the shape information is obtained through the proposed Extended Generalised Ridgelet-Fourier (EGRF). These features are fused together through a proposed integrated scheme. The feature fusion method has been tested on the SIMPLIcity image database, where several retrieval measurements are utilised to compare the effectiveness of the proposed method with few other comparable methods. The retrieval results show that the proposed Integrated Colour-shape (ICS) descriptor has successfully obtained the best overall retrieval performance in all the retrieval measurements as compared to the benchmark methods, which include precision (53.50%), precision at 11 standard recall levels (52.48%), and rank (17.40). Universiti Putra Malaysia Press 2013 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/40505/1/32.%20Content-based%20Image%20Retrieval%20Using%20Colour%20and%20Shape%20Fused.pdf Mustaffa, Mas Rina and Ahmad, Fatimah and Mahmod, Ramlan and Doraisamy, Shyamala (2013) Content-based image retrieval using colour and shape fused features. Pertanika Journal of Science & Technology, 21 (1). pp. 161-168. ISSN 0128-7680; ESSN: 2231-8526 http://www.pertanika.upm.edu.my/Pertanika%20PAPERS/JST%20Vol.%2021%20%281%29%20Jan.%202013/15.%20%20Page%20161-168.pdf |
| spellingShingle | Mustaffa, Mas Rina Ahmad, Fatimah Mahmod, Ramlan Doraisamy, Shyamala Content-based image retrieval using colour and shape fused features |
| title | Content-based image retrieval using colour and shape fused features |
| title_full | Content-based image retrieval using colour and shape fused features |
| title_fullStr | Content-based image retrieval using colour and shape fused features |
| title_full_unstemmed | Content-based image retrieval using colour and shape fused features |
| title_short | Content-based image retrieval using colour and shape fused features |
| title_sort | content-based image retrieval using colour and shape fused features |
| url | http://psasir.upm.edu.my/id/eprint/40505/ http://psasir.upm.edu.my/id/eprint/40505/ http://psasir.upm.edu.my/id/eprint/40505/1/32.%20Content-based%20Image%20Retrieval%20Using%20Colour%20and%20Shape%20Fused.pdf |