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A method for automatic identification of crop lines in drone images from a mango tree plantation using segmentation over YCrCb color space and Hough transform

机译:使用YCRCB颜色空间和Hough变换在芒果树种植园中自动识别芒果树种植术中的作物线的方法

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Today, several applications use machine vision to product quality control, military industry, health, agriculture, and others. The crop lines are important in agricultural production since they allow to maximize the crop area useful and autonomous navigation through the crop. The use of machine vision in crop lines has addressed problems such as planting, fertilization, plant protection, weeding, and harvesting. In this paper, a method for segmentation stage use both on Y.Cr.Cb Color Space and Hough transform to find the tree crop lines in U.A.V (unmanned aerial vehicles) images acquired over a mango tree plantation. The proposed method has 86 percent of efficiency.
机译:如今,几种应用程序使用机器愿景来产品质量控制,军事行业,健康,农业等。作物线在农业生产中是重要的,因为它们允许通过作物最大化作物区域有用和自主的导航。在作物线中使用机器视觉已经解决了种植,施肥,植物保护,除草和收获等问题。在本文中,用于分割阶段的方法在Y.CR.CB颜色空间和Hough变换上使用,以找到通过芒果树种植园获取的U.a.v(无人机航空车辆)图像中的树裁剪线。所提出的方法具有86%的效率。

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