NDLI: Automatic food recognition system for middle-eastern cuisines

Content Provider	IET Digital Library
Author	Qaraqe, Marwa Usman, Muhammad Ahmad, Kashif Sohail, Amir Boyaci, Ali
Abstract	The concerns for a healthier diet are increasing day by day, especially in diabetics wherein the aim of healthier diet can only be achieved by keeping a track of daily food intake and glucose-level. As a consequence, there is an ever-increasing need for automatic tools able to help diabetics to manage their diet and also help physicians to better analyse the effects of various types of food on the glucose-level of diabetics. In this paper, we propose an intelligent food recognition and tracking system for diabetics, which is potentially an essential part of a mobile application that we propose to couple food intake with the blood glucose-level using glucose measuring sensors. For food recognition, we rely on several feature extraction and classification techniques individually and jointly using an early and three different late fusion techniques, namely (i) Particle Swarm Optimisation (PSO), (ii) Genetic Algorithms (GA) based fusion and (iii) simple averaging. Moreover, we also evaluate the performance of several handcrafted and deep features and compare the results against state-of-the-art. In addition, we collect a large-scale dataset containing images from several types of local Middle-Eastern food, which is intended to become a powerful support tool for future research in the domain.
Starting Page	2469
Ending Page	2479
Page Count	11
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 11, Sep (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/11
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2019.1051
Journal	IET Image Processing
Publisher Date	2020-04-23
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Automatic Food Recognition System Automatic Tools Biology And Medical Computing Biomedical Measurement And Imaging Blood Blood Glucose Level Classification Technique Computer Vision And Image Processing Technique Daily Food Intake Diabetics Diseases Early Fusion Technique Feature Extraction Genetic Algorithm Genetic Algorithm-based Fusion Glucose Measuring Sonsor Health Physics Healthier Diet Image Classification Image Fusion Image Recognition Intelligent Food Recognition Knowledge Engineering Technique Large-scale Dataset Collection Local Middle-eastern Food Medical And Biomedical Uses of Field Medical Image Processing Middle-eastern Cuisines Mobile Application Object Tracking Optimisation Technique Particle Swarm Optimisation Patient Diagnostic Method And Instrumentation Radiations Radioactivity Sensor Fusion Sugar Tracking System
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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