Original Articles
Vol. 54 No. 1 (2023)
Key technology of crop precision sowing based on the vision principle
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All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Received: 31 May 2022
Accepted: 12 August 2022
Accepted: 12 August 2022
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The growth of crops is seriously affected in the process of precision planting of crops due to many external environmental interference factors, low precision of sowing technology, and large significant relative errors. To solve this problem, machine vision technology is introduced to study the key technology of crop precision sowing based on the vision principle. After pre-processing the crop image, the corresponding histogram is established. Then, the segmentation threshold method is used to gray the image and determine the best threshold to have a good recognition effect. Finally, according to the growth height and colour analysis of crops in the image, predict the growth of crops and realise the precision sowing of crops. The comparative experimental results show that under the application of the new sowing technology, the estimation accuracy of the crop planting area is high, the recognition accuracy of planting position is also high, and the fertilisation uniformity is close to the actual data, which can provide an important basis for improving the quality of crop sowing.
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How to Cite
“Key technology of crop precision sowing based on the vision principle” (2022) Journal of Agricultural Engineering, 54(1). doi:10.4081/jae.2022.1453.
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