This paper is published in Volume-4, Issue-3, 2018
Area
Healthcare
Author
Dheeraj Belliappa K S, Karan Vikram Singh Bhatia, Fathima Seher, Chinmita Shetty, Asha K S
Org/Univ
School of Engineering and Technology Jain University (SET JU), Bengaluru, Karnataka, India
Pub. Date
22 May, 2018
Paper ID
V4I3-1487
Publisher
Keywords
Raspberry Pi 3, Hx7111 Load Cell, 5MP Raspberry Pi camera, Matlab.

Citationsacebook

IEEE
Dheeraj Belliappa K S, Karan Vikram Singh Bhatia, Fathima Seher, Chinmita Shetty, Asha K S. Food recognition and analysis using image processing, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Dheeraj Belliappa K S, Karan Vikram Singh Bhatia, Fathima Seher, Chinmita Shetty, Asha K S (2018). Food recognition and analysis using image processing. International Journal of Advance Research, Ideas and Innovations in Technology, 4(3) www.IJARIIT.com.

MLA
Dheeraj Belliappa K S, Karan Vikram Singh Bhatia, Fathima Seher, Chinmita Shetty, Asha K S. "Food recognition and analysis using image processing." International Journal of Advance Research, Ideas and Innovations in Technology 4.3 (2018). www.IJARIIT.com.

Abstract

Some portion of what makes getting in shape so troublesome is that checking calories is a vague science at best. Eating food without knowledge of its composition and nutritional contents prompts poor processing leading to poor health. The Smork is an electronic fork that helps you to screen and track your dietary patterns. Each time you convey nourishment from the device it Indeed, even with nutritious data, one needs to screen serving sizes, people are continually searching for approaches to enhance their health and wellbeing. The typical procedure of getting nutritional data is by utilizing google or utilize some application, for example, Coach, Noom, Calorie Counter, Lose It. In this paper, we proposed to make this procedure more brilliant, speedier, and more proficient by building an electronic device that can demonstrate the nourishment data by just taking a photo of the meal. Using Raspberry Pi board as the core processing unit of the whole system a Weight sensor, HX711 Load Cell Module and a 5MP Raspberry Pi camera attached to the smart fork collects data and transmits it to a food database where it is compared with predefined food values and tallies the image using an image processing technique on Matlab platform. The smart-fork connects to the Android application using Bluetooth. We build up an android reality application to help clients to get nourishing data in a simple way. The data is shown as calorie, fat, starch, and protein per serving. Utilizing this application, clients can get the healthful data just by taking a photo of the food and not with standing cooking techniques to know exactly how much calories are being expended. SmartFork needs to do all the tallying, compiling, analysis and leave the users of the fork to just do the eating.