Strawberry Packaging Support System Based on Image Recognition.

2024 IEEE/SICE International Symposium on System Integration (SII)(2024)

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摘要
Strawberry packaging requires strict weight control and precise work for each pack. Owing to the fragility of the fruit, the quality of strawberries deteriorates when handled often; the mass has to be measured with minimal human contact. Hence, packaging work tends to increase the burden on skilled workers who can estimate weight by visual inspection. Moreover, the hiring of workers is problematic. In this study, by leveraging camera images, we developed a system based on image recognition that estimates strawberry mass and ripeness. This visualized information would enable inexperienced workers to perform appropriate tasks. The system can thus determine the optimal solution for appropriate strawberry packaging, enabling informed packaging decisions.
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关键词
Image Recognition,Skilled Workers,Illumination,Deep Learning,Machine Learning Models,Area Measurements,Object Detection,Dynamic Programming,Color Space,Pixel Level,Instance Segmentation,Masked Images,Pixel Count,Mass Estimates,Optimization Software,Red Hue,Fruit Mass,HSV Color
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