کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10278064 | 464410 | 2012 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Imaged based estimation of food volume using circular referents in dietary assessment
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی شیمی
مهندسی شیمی (عمومی)
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Imaged based estimation of food volume using circular referents in dietary assessment Imaged based estimation of food volume using circular referents in dietary assessment](/preview/png/10278064.png)
چکیده انگلیسی
Measuring food volume (portion size) is a critical component in both clinical and research dietary studies. With the wide availability of cell phones and other camera-ready mobile devices, food pictures can be taken, stored or transmitted easily to form an image based dietary record. Although this record enables a more accurate dietary recall, a digital image of food usually cannot be used to estimate portion size directly due to the lack of information about the scale and orientation of the food within the image. The objective of this study is to investigate two novel approaches to provide the missing information, enabling food volume estimation from a single image. Both approaches are based on an elliptical reference pattern, such as the image of a circular pattern (e.g., circular plate) or a projected elliptical spotlight. Using this reference pattern and image processing techniques, the location and orientation of food objects and their volumes are calculated. Experiments were performed to validate our methods using a variety of objects, including regularly shaped objects and food samples.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Food Engineering - Volume 109, Issue 1, March 2012, Pages 76-86
Journal: Journal of Food Engineering - Volume 109, Issue 1, March 2012, Pages 76-86
نویسندگان
Wenyan Jia, Yaofeng Yue, John D. Fernstrom, Ning Yao, Robert J. Sclabassi, Madelyn H. Fernstrom, Mingui Sun,