Related Experiment Video
Updated: Jun 10, 2026
07:47
Design and Evaluation of Smart Glasses for Food Intake and Physical Activity Classification
Published on: February 14, 2018
11.2K
Application of machine vision in food computing: A review
Zhiyao Zhao1, Rong Wang1, Minghao Liu1
1School of Computer and Artificial Intelligence, School of Light Industry Science and Engineering, Beijing Technology and Business University, Beijing 100048, China.
Food Chemistry
|October 5, 2024
Summary
Artificial intelligence (AI) and machine vision enhance the food industry through image recognition. This review covers AI applications in food safety, nutrition analysis, and process optimization for sustainable development.
Area of Science:
- Food Science and Technology
- Computer Science
- Artificial Intelligence
Background:
- Growing global intelligence and sustainable development awareness drive AI adoption in the food industry.
- Machine vision-based image recognition is a key AI technology for food computing applications.
Purpose of the Study:
- To review the current research status and future prospects of machine vision in food computing.
- To provide theoretical and technical guidance for integrating AI into the food sector.
Main Methods:
- Review of practical application cases in the food industry.
- Exploration of image recognition workflows.
- Analysis of traditional machine learning and deep learning methods.
Main Results:
- Image recognition, using both traditional and deep learning, is applied across food safety, nutrition analysis, process monitoring, and management optimization.
- The study highlights diverse applications of AI in enhancing food industry operations.
Conclusions:
- Machine vision-based image recognition offers significant potential for advancing the food industry.
- AI integration facilitates innovation and efficiency in food computing, supporting sustainable development goals.
Related Concept Videos
01:29Microbes in Food Production
Microbial fermentation is central to food biotechnology, enhancing flavor, texture, preservation, and stability. Fermentative microorganisms metabolize carbohydrates into organic acids, alcohols, and other metabolites that inhibit spoilage organisms and improve digestibility while contributing distinctive sensory qualities.In baking, amylases naturally present in flour hydrolyze starch into monosaccharides such as glucose, which Saccharomyces cerevisiae ferments anaerobically. Through...
01:29Sources of Food Contamination
Contamination of food by microbial agents and natural toxins poses significant risks to public health. These hazards can be introduced at various points across the food supply chain, ranging from environmental sources to processing and storage stages. Understanding these contamination pathways is critical for developing strategies to ensure food safety.Seafood is particularly vulnerable to contamination through both environmental exposure and microbial colonization. Toxins from harmful algal...
01:27Principles of Food Preservation
Food spoilage results from microbial growth, enzymatic activity, and environmental factors that gradually degrade the sensory, nutritional, and safety qualities of food. Preservation techniques aim to slow or halt these processes to extend shelf life and maintain product quality.A key concept in food microbiology is the microbial growth curve, which includes four phases: lag, exponential (log), stationary, and death. During the lag phase, bacteria adjust to their environment without significant...