Paper Details

One of the cutting edge fields right now are deep learning and computer vision. Using this we develop a mobileapp that takes a snap shot of the food we eat daily and recognize the amount of calorie and nutritional value present in thefood. It also posts a label whether the food is recommended for a diabetes patient or not. Because of this application, thepatient knows whether he can consume the food or not. Thus prevents the patient from various health issues. A good dietarymonitoring is also maintained by referring huge amount of data sets, since there are lots of different kinds of foods availablein the world. The biggest advantage is that this application does not require the usage of internet and hence can be usedanywhere at any time. Food recognition is based on the color, texture and size using various algorithms. Our system canperform automatic food detection and recognition in real-life settings. These settings include cluttered background images.Our system will also be able to identify multiple varieties of food present on a plate and simultaneously estimate their portionsize.

Krithika Nagarajan, M.Aishwarya, Dr.L.JabaSheela, “Pixel Bites-Estimation of Food Calorie For Diabetes Patients Using Deep Learning And Computer Vision”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 5, Issue 3, pp. 803-807, March 2018.