Efficient superpixel based segmentation for food image analysis
In this paper, we propose a segmentation method based on normalized cut and superpixels. The method relies on color and texture cues for fast computation and efficient use of memory. The method is used for food image segmentation as part of a mobile food record system we have developed for dietary a...
| Main Authors: | , , , , |
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| Format: | Conference Paper |
| Published: |
2016
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| Online Access: | http://hdl.handle.net/20.500.11937/51133 |
| _version_ | 1848758623587532800 |
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| author | Wang, Y. Liu, C. Zhu, F. Boushey, Carol Delp, E. |
| author_facet | Wang, Y. Liu, C. Zhu, F. Boushey, Carol Delp, E. |
| author_sort | Wang, Y. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | In this paper, we propose a segmentation method based on normalized cut and superpixels. The method relies on color and texture cues for fast computation and efficient use of memory. The method is used for food image segmentation as part of a mobile food record system we have developed for dietary assessment and management. The accurate estimate of nutrients relies on correctly labelled food items and sufficiently well-segmented regions. Our method achieves competitive results using the Berkeley Segmentation Dataset and outperforms some of the most popular techniques in a food image dataset. |
| first_indexed | 2025-11-14T09:46:56Z |
| format | Conference Paper |
| id | curtin-20.500.11937-51133 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:46:56Z |
| publishDate | 2016 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-511332017-09-13T15:50:27Z Efficient superpixel based segmentation for food image analysis Wang, Y. Liu, C. Zhu, F. Boushey, Carol Delp, E. In this paper, we propose a segmentation method based on normalized cut and superpixels. The method relies on color and texture cues for fast computation and efficient use of memory. The method is used for food image segmentation as part of a mobile food record system we have developed for dietary assessment and management. The accurate estimate of nutrients relies on correctly labelled food items and sufficiently well-segmented regions. Our method achieves competitive results using the Berkeley Segmentation Dataset and outperforms some of the most popular techniques in a food image dataset. 2016 Conference Paper http://hdl.handle.net/20.500.11937/51133 10.1109/ICIP.2016.7532818 restricted |
| spellingShingle | Wang, Y. Liu, C. Zhu, F. Boushey, Carol Delp, E. Efficient superpixel based segmentation for food image analysis |
| title | Efficient superpixel based segmentation for food image analysis |
| title_full | Efficient superpixel based segmentation for food image analysis |
| title_fullStr | Efficient superpixel based segmentation for food image analysis |
| title_full_unstemmed | Efficient superpixel based segmentation for food image analysis |
| title_short | Efficient superpixel based segmentation for food image analysis |
| title_sort | efficient superpixel based segmentation for food image analysis |
| url | http://hdl.handle.net/20.500.11937/51133 |