Abstract
In the production process of edible fungi, the quality inspection of each link is a very important link, and the inspection link determines the reliability and intelligence of intelligent equipment. The precision sealing technology of the cotton ball is the last step of the bacteria bag injection, and the quality of the sealing directly affects the bacteria release rate of the bacteria bag. To this end, this paper designs a diagnostic system for the sealing quality of edible fungus bag cotton balls based on image processing technology. In this system, image enhancement, region segmentation and noise filtering are used to preprocess the picture; the combination of convolutional neural network technology and image recognition technology detects the sealing quality of the cotton ball of edible fungus bag, and convolution the neural network uses a three-layer convolution structure. Through a large number of sample training, the accuracy of the identification of the quality of the bacterial envelope is as high as 99.8%.
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Acknowledgements
This work was supported by Jilin Province Science and Technology Development Plan Item (No. 20200401110GX).
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Yang, X., Mao, C., Yang, Z., Liu, H. (2021). Sealing Detection Technology of Cotton Ball of Edible Fungus Bag. In: Atiquzzaman, M., Yen, N., Xu, Z. (eds) Big Data Analytics for Cyber-Physical System in Smart City. BDCPS 2020. Advances in Intelligent Systems and Computing, vol 1303. Springer, Singapore. https://doi.org/10.1007/978-981-33-4572-0_75
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DOI: https://doi.org/10.1007/978-981-33-4572-0_75
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