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Vision Based Crop Row Detection for Low Cost UAV Imagery in Organic Agriculture

机译:基于视觉的有机农业低成本UAV图像的作物行检测

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Unmanned aerial vehicles (UAVs) and autonomous smart farming robots are a great solution to reduce the use of chemical or synthetic pesticides. One of the critical aspects of these systems are the requirement to follow the crop rows without damaging the plants or the dam. In this paper, a system was developed which enables a semi-autonomous flight by means of crop row detection in organic agriculture. The system consists of a Raspberry Pi microcontroller with a camera and uses a number of image processing methods to detect plant rows. The evaluation of images of different crop row fields and of crop row models showed that all different plant rows were reliably detected. A runtime evaluation showed that the computing power of the microcontroller for the application is limited. Optimizations such as reducing the image size and adapting calculation-intensive methods resulted in a frame rate of 8 to 12 FPS. This processing time is sufficient for a slow UAV flight.
机译:无人驾驶航空公司(无人机)和自主智能养殖机器人是减少化学或合成杀虫剂的使用的伟大解决方案。 这些系统的关键方面之一是要求在不损坏植物或大坝的情况下遵循作物行。 在本文中,开发了一种系统,其能够通过有机农业的作物行检测来实现半自主飞行。 该系统由带有相机的覆盆子PI微控制器组成,并使用许多图像处理方法来检测工厂行。 对不同裁剪行场和作物行模型的图像的评估显示,所有不同的植物行被可靠地检测到。 运行时评估表明,应用程序的微控制器的计算能力是有限的。 优化,例如降低图像尺寸和调整计算密集型方法,导致帧速率为8到12 fps。 这种处理时间足以让缓慢的UAV飞行。

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