An effective method for combining multiple features of image retrieval
We propose an image retrieval system using the Borda count method in combining multiple experts (CME). It combines color-, shape- and texture-based retrieval systems. CME method can complementarily combine results of each retrieval system, which uses different features. There are some problems when...
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| container_end_page | 985 vol.2 |
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| creator | Seyoon Jeong Kyuheon Kim Byungtae Chun Jaeyeon Lee Bae, Y.J. |
| description | We propose an image retrieval system using the Borda count method in combining multiple experts (CME). It combines color-, shape- and texture-based retrieval systems. CME method can complementarily combine results of each retrieval system, which uses different features. There are some problems when the Borda count method in pattern recognition is applied to image retrieval. Thus, we propose a modified Borda count method to solve these problems. In the experiment our method reduces false positive errors and produces better results than that of each retrieval module that uses only one feature. |
| doi_str_mv | 10.1109/TENCON.1999.818585 |
| format | Conference Proceeding |
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| identifier | ISBN: 0780357396 |
| ispartof | Proceedings of IEEE. IEEE Region 10 Conference. TENCON 99. 'Multimedia Technology for Asia-Pacific Information Infrastructure' (Cat. No.99CH37030), 1999, Vol.2, p.982-985 vol.2 |
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| language | eng |
| recordid | cdi_ieee_primary_818585 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Content based retrieval Equations Fuzzy neural networks Image processing Image retrieval Laboratories Pattern recognition Shape Software Telecommunication computing |
| title | An effective method for combining multiple features of image retrieval |
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