Food image analysis: Segmentation, identification and weight estimation
We are developing a dietary assessment system that records daily food intake through the use of food images taken at a meal. The food images are then analyzed to extract the nutrient content in the food. In this paper, we describe the image analysis tools to determine the regions where a particular...
| Main Authors: | , , , , |
|---|---|
| Format: | Conference Paper |
| Published: |
2013
|
| Online Access: | http://hdl.handle.net/20.500.11937/50154 |
| _version_ | 1848758407902789632 |
|---|---|
| author | He, Y. Xu, C. Khanna, N. Boushey, Carol Delp, E. |
| author_facet | He, Y. Xu, C. Khanna, N. Boushey, Carol Delp, E. |
| author_sort | He, Y. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | We are developing a dietary assessment system that records daily food intake through the use of food images taken at a meal. The food images are then analyzed to extract the nutrient content in the food. In this paper, we describe the image analysis tools to determine the regions where a particular food is located (image segmentation), identify the food type (feature classification) and estimate the weight of the food item (weight estimation). An image segmentation and classification system is proposed to improve the food segmentation and identification accuracy. We then estimate the weight of food to extract the nutrient content from a single image using a shape template for foods with regular shapes and area-based weight estimation for foods with irregular shapes. |
| first_indexed | 2025-11-14T09:43:30Z |
| format | Conference Paper |
| id | curtin-20.500.11937-50154 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:43:30Z |
| publishDate | 2013 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-501542018-03-29T09:09:27Z Food image analysis: Segmentation, identification and weight estimation He, Y. Xu, C. Khanna, N. Boushey, Carol Delp, E. We are developing a dietary assessment system that records daily food intake through the use of food images taken at a meal. The food images are then analyzed to extract the nutrient content in the food. In this paper, we describe the image analysis tools to determine the regions where a particular food is located (image segmentation), identify the food type (feature classification) and estimate the weight of the food item (weight estimation). An image segmentation and classification system is proposed to improve the food segmentation and identification accuracy. We then estimate the weight of food to extract the nutrient content from a single image using a shape template for foods with regular shapes and area-based weight estimation for foods with irregular shapes. 2013 Conference Paper http://hdl.handle.net/20.500.11937/50154 10.1109/ICME.2013.6607548 restricted |
| spellingShingle | He, Y. Xu, C. Khanna, N. Boushey, Carol Delp, E. Food image analysis: Segmentation, identification and weight estimation |
| title | Food image analysis: Segmentation, identification and weight estimation |
| title_full | Food image analysis: Segmentation, identification and weight estimation |
| title_fullStr | Food image analysis: Segmentation, identification and weight estimation |
| title_full_unstemmed | Food image analysis: Segmentation, identification and weight estimation |
| title_short | Food image analysis: Segmentation, identification and weight estimation |
| title_sort | food image analysis: segmentation, identification and weight estimation |
| url | http://hdl.handle.net/20.500.11937/50154 |