In this study, a visual grading system of vegetable grafting machine was developed. The study described key technology of\nvisual grading system of vegetable grafting machine. First, the contrasting experiment was conducted between acquired\nimages under blue background light and natural light conditions, with the blue background light chosen as lighting source.\nThe Visual C++ platform with open-source computer vision library (Open CV) was used for the image processing.\nSubsequently, maximum frequency of total number of 0-valued pixels was predicted and used to extract the measurements\nof scion and rootstock stem diameters. Finally, the developed integrated visual grading system was experimented\nwith 100 scions and rootstock seedlings. The results showed that success rate of grading reached up to 98%. This shows\nthat selection and grading of scion and rootstock could be fully automated with this developed visual grading system.\nHence, this technology would be greatly helpful for improving the grading accuracy and efficiency.
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