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http://dx.doi.org/10.9708/jksci.2017.22.05.057

Mobile Application based on Image Processing and a Proportion for Food Intake Measuring  

Kim, Do-Hyeon (Dept. of Computer and Communications Engineering, Kangwon National University)
Kim, Yoon (Dept. of Computer and Communications Engineering, Kangwon National University)
Han, Yu-Ri (Dept. of Preventive Medicine, Kangwon National University School of Medicine)
Publication Information
Journal of the Korea Society of Computer and Information / v.22, no.5, 2017 , pp. 57-63 More about this Journal
Abstract
In the paper, we propose a new reliable technique for measuring food intake based on image automatically without user intervention. First, food and bowl image before and after meal is obtained by user. The food and the bowl are divided into each region by the K-means clustering, Otsu algorithm, Morphology, etc. And the volume of food is measured by a proportional expression based on the information of the container such as it's entrance diameter, depth, and bottom diameter. Finally, our method calculates the volume of the consumed food by the difference between before and after meal. The proposed technique has higher accuracy than existing method for measuring food intake automatically. The experiment result shows that the average error rate is up to 7% for three types of containers. Computer simulation results indicate that the proposed algorithm is a convenient and accurate method of measuring the food intake.
Keywords
Food intake; Image-based volumetric algorithm; Image segmentation; Mobile application; 3D estimation;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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1 M. Haralick and S.R. Sternberg, "Image analysis using mathematical morphology", IEEE Transactions on PAMI, Vol.9, No.4, pp. 532-550, 1987.
2 R.C. Gonzalez and R.E. Woods, "Digital Image Processing", Kyobobook, pp. 550-560, 2002.
3 Q&A on the carcinogenicity of the consumption of red meat and processed meat, http://www.iarc.fr/en/mdeiia-centre/iarcnews/pdf/Monographs-Q&A_Vol114.pdf
4 H.Y. Choi and J.G. Kim "A study on Consumer Wellbeing Trends of Korea", KSVB, Vol.10, No.4, pp. 81-93, 2015.
5 T.J. Choi, E.S. Kim and H.M. Lee, "Algorithms to convert 2D image into a 3D model", Proceedings of the Korea Contents Association Conference, pp. 347-348, 2015.
6 J.Y. Kim, H.S. Kim and K.N. Kim, "A study on nutritional intakes in middle income adults based on data from the 5th Korean National Health and Nutrition Examination Survey", Journal of Nutrition and Health, Vol.48, No.4, pp. 364-370, 2015.   DOI
7 H.R. Kim, "A Study on the Association of Diet Quality and Risk of Mortality and Major Chronic Diseases from Nationally Representative Longitudinal Data", Korea Institute for Health and Social Affairs, Vol.33, No.3, pp. 5-30, 2013.
8 B.K. Lim, J.S. Kim, J.H. Yoo and B.T. Zhang, "DietAdviser : A Personalized eHealth Agent in a Mobile Computing Enviroment", Journal of KIISE : Computing Practices and Letters, Vol. 18, No. 6, pp. 459-463, 2012.
9 S.Y. Jung, S.H. Ryu and G. G. Lee, "DietTalk : Diet and Health Assistant Based on Spoken Dialog System", Winter Conference of KIISE, pp. 1681-1683, 2014.
10 M.H. Kim and H.K. Hong, "2D - 3D Conversion Method Based on Scene Space Reconstruction", The Journal of the Korea Contents Association, Vol.14, No.7, pp. 1-9, 2014.   DOI
11 I.S. Kim, H.T. Kim and J.S. Youn, "A Study on 2D-3D Image Conversion using Depth Map Chart Analysis", KSCI, Vol.23, No.1, pp. 205-208, 2015.
12 T. Kanungo, D.M. Mount and N.S. Netanyahu, "An efficient k-means clustering algorithm: Analysis and implementation", IEEE Transactions on PAMI, Vol.24, No.7, pp. 881-892, 2002.   DOI
13 L. Lucchese and S. Mitray, "color image segmentation: A state-of-theart survey", Proceedings of the Indian National Science Academy, pp. 207-221, 2001.
14 Q. Chen, et al., "Modified two-dimensional otsu image segmentation algorithm and fast realisation", IET Image Processing, Vol.6, No.4, pp. 426-433, 2012.   DOI