Image enhancement and quality measures for dietary assessment using mobile devices
Measuring accurate dietary intake is considered to be an open research problem in the nutrition and health fields. We are developing a system, known as the mobile device food record (mdFR), to automatically identify and quantify foods and beverages consumed based on analyzing meal images captured wi...
| Main Authors: | , , , , |
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| Format: | Conference Paper |
| Published: |
2012
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| Online Access: | http://hdl.handle.net/20.500.11937/51079 |
| _version_ | 1848758609010229248 |
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| author | Xu, C. Zhu, F. Khanna, N. Boushey, Carol Delp, E. |
| author_facet | Xu, C. Zhu, F. Khanna, N. Boushey, Carol Delp, E. |
| author_sort | Xu, C. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Measuring accurate dietary intake is considered to be an open research problem in the nutrition and health fields. We are developing a system, known as the mobile device food record (mdFR), to automatically identify and quantify foods and beverages consumed based on analyzing meal images captured with a mobile device. The mdFR makes use of a fiducial marker and other contextual information to calibrate the imaging system so that accurate amounts of food can be estimated from the scene. Food identification is a difficult problem since foods can dramatically vary in appearance. Such variations may arise not only from non-rigid deformations and intra-class variability in shape, texture, color and other visual properties, but also from changes in illumination and viewpoint. To address the color consistency problem, this paper describes illumination quality assessment methods implemented on a mobile device and three post color correction methods. |
| first_indexed | 2025-11-14T09:46:42Z |
| format | Conference Paper |
| id | curtin-20.500.11937-51079 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:46:42Z |
| publishDate | 2012 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-510792018-03-29T09:09:26Z Image enhancement and quality measures for dietary assessment using mobile devices Xu, C. Zhu, F. Khanna, N. Boushey, Carol Delp, E. Measuring accurate dietary intake is considered to be an open research problem in the nutrition and health fields. We are developing a system, known as the mobile device food record (mdFR), to automatically identify and quantify foods and beverages consumed based on analyzing meal images captured with a mobile device. The mdFR makes use of a fiducial marker and other contextual information to calibrate the imaging system so that accurate amounts of food can be estimated from the scene. Food identification is a difficult problem since foods can dramatically vary in appearance. Such variations may arise not only from non-rigid deformations and intra-class variability in shape, texture, color and other visual properties, but also from changes in illumination and viewpoint. To address the color consistency problem, this paper describes illumination quality assessment methods implemented on a mobile device and three post color correction methods. 2012 Conference Paper http://hdl.handle.net/20.500.11937/51079 10.1117/12.909949 restricted |
| spellingShingle | Xu, C. Zhu, F. Khanna, N. Boushey, Carol Delp, E. Image enhancement and quality measures for dietary assessment using mobile devices |
| title | Image enhancement and quality measures for dietary assessment using mobile devices |
| title_full | Image enhancement and quality measures for dietary assessment using mobile devices |
| title_fullStr | Image enhancement and quality measures for dietary assessment using mobile devices |
| title_full_unstemmed | Image enhancement and quality measures for dietary assessment using mobile devices |
| title_short | Image enhancement and quality measures for dietary assessment using mobile devices |
| title_sort | image enhancement and quality measures for dietary assessment using mobile devices |
| url | http://hdl.handle.net/20.500.11937/51079 |