Application of machine vision in food computing: A review.

Journal: Food chemistry
Published Date: Sep 23, 2024

Abstract

With global intelligence advancing and the awareness of sustainable development growing, artificial intelligence technology is increasingly being applied to the food industry. This paper, grounded in practical application cases, reviews the current research status and prospects of machine vision-based image recognition technology in food computing. It explores the general workflow of image recognition, applications based on traditional machine learning and deep learning methods. The paper covers areas including food safety detection, dietary nutrition analysis, process monitoring, and enterprise management model optimization. The aim is to provide a solid theoretical foundation and technical guidance for the integration and cross-fertilization of the food industry with artificial intelligence technology.

Authors

  • Zhiyao Zhao
    Beijing Technology and Business University, Beijing, China.
  • Rong Wang
    College of Food Science and Engineering, Northwest A&F University, Yangling 712100, Shanxi, China. Electronic address: wangrong91@nwsuaf.edu.cn.
  • Minghao Liu
    Key Laboratory for Molecular Enzymology and Engineering of Ministry of Education, School of Life Science, Jilin University, 2699 Qianjin Street, Changchun, 130012, China. Electronic address: lmh23@mails.jlu.edu.cn.
  • Lin Bai
    School of Computer and Artificial Intelligence, School of Light Industry Science and Engineering, Beijing Technology and Business University, Beijing 100048, China. Electronic address: 2230402043@st.btbu.edu.cn.
  • Ying Sun
    CFAR and I2R, Agency for Science, Technology and Research, Singapore.

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