Recipe Recommendation based on Food Ingredients Recognition using Deep Learning

DOI

10.2991/978-94-6463-589-8_52How to use a DOI?

Keywords

Recipe Recommendation; YOLO; Food; Deep Learning; Image Recognition

Abstract

Every individual requires food for nutritional support, without which the body suffers from various diseases such as gastric issues and low blood sugar. While there are many recipe websites, finding a suitable recipe can be time-consuming, especially for those who lack cooking knowledge with available ingredients. This project addresses this challenge by developing a recipe recommendation model using a deep learning algorithm to suggest recipes based on recognized food ingredients. The model utilizes more than 2,000 images categorized into three food ingredient groups: rice, apple, and chicken. The data collection process includes thorough preprocessing, data cleaning, and annotation. The dataset is then augmented and split into training, validation, and testing sets in an 80–10-10 ratio. To build the food ingredient recognition model, the You Only Look Once (YOLO) technique, specifically YOLOv8, is employed. The system is designed as a web-based application, providing an accessible interface for users. After extensive training, validation, and testing, the model achieved an impressive accuracy of 98%, demonstrating its capability to accurately detect the specified ingredients. Future research aims to enhance the system's functionality by addressing current limitations. Planned improvements include integrating a comprehensive database for storing recipes, which would facilitate easier data insertion and the addition of nutritional information for each recipe. Furthermore, incorporating live-camera integration could enhance user engagement and practicality.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Muhamad Ridhwan Mohamad Razali
AU  - Hana Fakhira Almarzuki
AU  - Rabiahtul Adawiyah Bahar
AU  - Nur Atiqah Sia Abdullah
PY  - 2024
DA  - 2024/12/01
TI  - Recipe Recommendation based on Food Ingredients Recognition using Deep Learning
BT  - Proceedings of the International Conference on Innovation & Entrepreneurship in Computing, Engineering & Science Education (InvENT 2024)
PB  - Atlantis Press
SP  - 555
EP  - 564
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-589-8_52
DO  - 10.2991/978-94-6463-589-8_52
ID  - Razali2024
ER  -