Feasibility of Food Recognition and Calorie Estimation of Fast Food and Healthy Meals Available in the Philippines

K. Dy, J. Ligan, M. Cabatuan

Abstract


This paper presents the design and development of a food recognition smartphone application which can also display the estimated calorie/s of the food itself. It is intended for people who would like to monitor their diet through food calorie intake measurement (i.e. user’s daily calorie intake record). It is equipped with a food database consisting of typical fruits and vegetables commonly found in the Philippines. As part of the study, it also includes some of the meals in food chains (i.e. McDonald's, and The Healthy Corner) found in the Philippines where the calorie information is readily available. The result shows 82.86 % accuracy for the top-1 category, and 99.29 % for the top-5 category. The algorithm being used in this project is Artificial Neural Network (ANN) wherein the recognition process must properly be achieved. Furthermore, the aforementioned database is supported by TensorFlow which is an open-source software library for Machine Intelligence.

Keywords


Artificial Neural Network; Calorie; Food Recognition; TensorFlow;

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References


World Health Organization, "The Impact of Chronic Disease in the Philippines," 2010. [Online]. Available: http://www.who.int/chp/chronic_disease_report/philippines.pdf

Harvard T. H. Chan: School of Public Health, "Obesity Causes," [Online]. Available: http://www.hsph.harvard.edu/obesity-preventionsource/obesity-causes.

M. Santiago, "Nutritional Content In Menu Boards Act of 2008," 2008 October. [Online]. Available: http://senate.gov.ph/lis/bill_res.aspx?congress=14&q=SBN-2682

K. Ruan and L. Shao, "Calorie Estimation from Fast Food Images," 12 December 2015. [Online]. Available: http://cs229.stanford.edu/proj2015/151_report.pdf. [Accessed 19 February 2017].

Y. Kawano and K. Yanai, "Food Image Recognition with Deep Convolutional Features," 13 September 2014. [Online]. Available: http://ubicomp.org/ubicomp2014/proceedings/ubicomp_adjunct/work shops/CEA/p589-kawano.pdf. [Accessed 26 February 2017].

"EngineersGarage: Introduction to Image Processing," 2012. [Online]. Available: http://www.engineersgarage.com/articles/imageprocessing-tutorial-applications. [Accessed 1 December 2015].

TechTarget, "Definition: Machine Learning," 2015. [Online]. Available: http://whatis.techtarget.com/definition/machine-learning. [Accessed 1 December 2015].

SAS Institute Inc., "Machine Learning: What it is & why it matters," [Online]. Available: http://www.sas.com/en_us/insights/analytics/machine-learning.html. [Accessed 1 December 2015].

F.-F. Li, "Machine Learning in Computer Vision," [Online]. Available: https://www.cs.princeton.edu/courses/archive/spring07/cos424/lecture s/li-guest-lecture.pdf. [Accessed 1 December 2015].

S. Lucci and D. Kopec, Artificial Intelligence in the 21st Century: A Living Introduction, Dulles, Virginia: David Pallai, 2013.

R. Elmasri and S. B. Navathe, Fundamentals of Database Systems: Seventh Edition, New Jersey: Pearson Higher Education, 2016.

J. Painter, "How do food manufacturers calculate the calorie count of packaged foods?," 2016. [Online]. Available: http://www.scientificamerican.com/article/how-do-foodmanufacturers/.

American Dietetic Association and American Diabetes Association, "Food Exchange Lists," 2008. [Online]. Available: http://dtc.ucsf.edu/pdfs/FoodLists.pdf.

S. W. Lichtman, K. Pisarska, E. R. Berman, M. Pestone, H. Dowling, E. Offenbacher, H. Weisel, S. Heshka, D. E. Matthews and S. B. Heymsfield, "Discrepancy between Self-reported and Actual Caloric Intake and Exercise in Obese Subjects," The New England Journal of Medicine, 1992.

A. Myers, N. Johnston, V. Rathod, A. Korattikara, A. Gorban, N. Silberman, S. Guadarrama, G. Papandreou, J. Huang and K. Murphy, "Im2Calories: towards an automated mobile vision food diary," [Online]. Available: https://www.cs.ubc.ca/%7Emurphyk/Papers/im2calories_iccv15.pdf


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