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Detection technology of plant protection equipment nozzle based on machine vision

机译:基于机器视觉的植保设备喷嘴检测技术

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摘要

In this paper, we present a method of using machine vision technology to detect the nozzle of plant protection equipment through two spray variables (spray angle and spray volume distribution area), which provides a good experimental direction to improve the performance of the nozzle of plant protection equipment. Firstly, we get the images information with different backgrounds and shooting angles. Secondly, we process the images by edge detection, mathematical morphology and other related digital image processing techniques. Thirdly, we obtain the target area of spray angle and fog quantity distribution using the Hough transform line detection algorithm and pixel method. Finally, we compare the area and angle with the reference values to judge the rationality of the method and establish the error range. Experimental results show that the feature variable values are ideal for plant protection equipment nozzle spray angle and spray volume distribution area. It is proved that the feasibility of our method.
机译:本文提出了一种利用机器视觉技术通过两个喷雾变量(喷雾角度和喷雾体积分布面积)检测植物保护设备喷嘴的方法,为提高植物喷嘴性能提供了良好的实验方向。保护设备。首先,我们获得了具有不同背景和拍摄角度的图像信息。其次,我们通过边缘检测,数学形态学和其他相关的数字图像处理技术来处理图像。第三,利用霍夫变换线检测算法和像素法获得了喷雾角度和雾量分布的目标区域。最后,我们将面积和角度与参考值进行比较,以判断该方法的合理性并确定误差范围。实验结果表明,该特征变量值是植物保护设备喷嘴喷雾角度和喷雾量分布区域的理想选择。证明了我们方法的可行性。

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