Crop ripeness identification method

Abstract

The invention relates to a crop ripeness identification method. The method comprises the following steps: (1) providing a crop ripeness identification platform based on unmanned aerial vehicle detection, wherein the identification platform comprises a mobile hard disk drive, image acquisition equipment, image processing equipment and a digital signal processor, the digital signal processor is respectively connected with the image acquisition equipment and the image processing equipment; starting the image acquisition equipment and the image processing equipment after the unmanned aerial vehicle reaches a crop ripeness acquisition area, wherein the image acquisition equipment is used for shooting the acquisition area so as to acquire the crop area image; the image processing equipment is used for performing image processing on the crop area image; the digital signal processor is used for determining the crop ripeness in the acquisition area according to the image processing result; and the mobile hard disk drive is connected with the digital signal processor so as to store the crop ripeness in the acquisition area; and (2) operating the system.

Description

technical field [0001] The invention relates to the field of unmanned aerial vehicle monitoring, in particular to a method for identifying the maturity of crops. Background technique [0002] The traditional crop planting method is a decentralized planting mode based on the farmer. The adjacent farmlands belong to different farmers, and the farmers have different types of crops and different planting habits, resulting in uneven maturity of the crops planted. This kind of planting mode is also difficult to use large-scale mechanical tools for unified crop harvesting or picking at the same time. Farmers can only judge the maturity of crops in their own farmland based on personal experience, and when judging maturity, organize people individually on a family basis. harvest. [0003] With the development of crop planting mode from decentralized planting mode to intensive planting mode, many adjacent farmlands may belong to the same agricultural management department, and the sa...

AI Technical Summary

Problems solved by technology

[0004] However, in today’s intensive large-scale planting of the same crop, the judgment of maturity still relies on backward manual methods. When this method is applied to the judgment of the maturity of large-scale crops, the following problems will arise: (1) The reach of human eyes limited, the current crops may be mature, but most of the crops that are not touched by human eyes are immature, and harvesting at this time will cause huge economic losses to the agricultural management department; (2) the way of manual judgment is too dependent on personal experience, and its judgment There is a certain error between the results and the standard results

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