A Study of Automatic Judgment of Food Color and Cooking Conditions with Artificial Intelligence Technology

Abstract

In this study, the machine vision and artificial intelligence algorithms were used to rapidly check the degree of cooking of foods and avoid the over-cooking of foods. Using a smart induction cooker for heating, the image processing program automatically recognizes the color of the food before and after cooking. The new cooking parameters were used to identify the cooking conditions of the food when it is undercooked, cooked, and overcooked. In the research, the camera was used in combination with the software for development, and the real-time image processing technology was used to obtain the information of the color of the food, and through calculation parameters, the cooking status of the food was monitored. In the second year, using the color space conversion, a novel algorithm, and artificial intelligence, the foreground segmentation was used to separate the vegetables from the background, and the cooking ripeness, cooking unevenness, oil glossiness, and sauce absorption were calculated. The image color difference and the distribution were used to judge the cooking conditions of the food, so that the cooking system can identify whether or not to adopt partial tumbling, or to end a cooking operation. A novel artificial intelligence algorithm is used in the relative field, and the error rate can be reduced to 3%. This work will significantly help researchers working in the advanced cooking devices.

Application of digital-intelligence technology in the processing of Chinese materia medica

“… Zheng et al (2022) used cluster analysis and Artificial neural network analysis (ANN) to better identify gardenia with various processing degrees. For the determination of the end point of processing, the color difference and distribution in the image may be used to determine the degree of stir-frying and cooking of the drug, so that the processing system may determine whether to use partial tumbling, or to end the processing when the decoction pieces reach the optimal efficacy; such processing system may avoid improper or excessive processing ( Lin et al, 2021 ). By combining bionic sensors with chemometrics, the overall quality evaluation system of decoction pieces was established and used to determine whether the processing time of decoction pieces reached sufficient with the most optimized quality ( Zhang et al, 2023 ).…”

Review of The Application of Digital Transformation in Food Industry

“…These systems can even stop the cooking process automatically to prevent overcooking. The food is categorized as overcooked, cooked, or uncooked and stirred by a robotic arm (Lin et al, 2021). Moreover, a proposal for a neural network and recommendationintegrated system that specializes in Thai cuisine has been suggested.…”

Study on Multifactor Control Experiment and Design of Quality Detection System for Yuba Skin Production

“…In the process of the conjunctiva of Yuba skin, different grades of Yuba skin have some differences in texture and morphology. erefore, the extraction of texture features of Yuba skin can be used for image feature description carefully [14][15][16].…”