Design and Development of Mobile App for Food Recognition
Chandrasekaran. G1, Murugachandrave l.J2, Neethidevan. V3, Karthikeyan. A4
1Chandrasekaran. G, Department of MCA, Mepco Schlenk Engineering College, Sivakasi (Tamil Nadu), India.
2Murugachandrave l.J, Department of MCA, Mepco Schlenk Engineering College, Sivakasi (Tamil Nadu), India.
3Neethidevan. V, Department of MCA, Mepco Schlenk Engineering College, Sivakasi (Tamil Nadu), India.
4Karthikeyan. A, Department of MCA, Mepco Schlenk Engineering College, Sivakasi (Tamil Nadu), India.
Manuscript received on 22 April 2019 | Revised Manuscript received on 04 May 2019 | Manuscript Published on 17 May 2019 | PP: 47-49 | Volume-7 Issue-6S4 April 2019 | Retrieval Number: F10090476S419/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Obesity is one of the major problems many of the people are facing today. Obesity occurs because of excessive intake of food and lesser physical exercise or no physical exercise. A limited number of cases are due to genetics, medical reasons, or psychiatric illness. In order to have a balanced diet, we need to track the food calories, proteins, and minerals. It is hard to search each and every time about nutritional facts and also it is time consuming. In “Food Lens app”, simple snap of food photo will pop up all nutritional facts about the food and will be displayed in a user-friendly manner. Food Lens app uses modern Deep Learning methods to predict the food and related nutritional facts mapped in a faster manner. Now this app is able to predict ten different continental foods which have excess calories. So, this app prevents the users from taking excess calorie food or would assist them to take proper food periodically.
Keywords: Obesity, Food lens, Convolutional Neural Network (CNN).
Scope of the Article: Mobile App Security and Privacy