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Research on Recognition Technology of Caragana korshinskii Main Stem Used to Keep Stubble at a Certain Height after Cutting

机译:柠条主茎扦插留茬识别技术研究

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In order to meet the agronomic requirements of Caragana korshinskii for keeping stubble at a certain height after cutting it. This paper analyzes the color characteristics of Caragana korshinskii and withered grass, green grass, sky, twigs and other background noises in different color spaces. It is determined that the RGB color model with a large difference between the characteristic values of Caragana korshinskii and the background is used to process the image. The image is grayed by extracting the R-value component and G-value component that have a large difference between the characteristic values of Caragana korshinskii and the background noise, and the image is also grayed by the weighted average method. By comparison, it is determined that the graying method of extracting G value component with better segmentation effect should be adopted. The use of histogram equalization makes the image gray level evenly distributed, reducing the influence of light on the brightness of the image. The optimal threshold for image binarization is determined, and the median filter is used to eliminate salt and pepper noise. Corrosion, removal of small areas, expansion and other operations are performed on the image, and the twigs and hollows on the main stem are eliminated and filled. Using the least square method and using the polyfit function, the repair and fitting of the main stems of Caragana korshinskii are realized. Threshold segmentation algorithm was used to identify the main stem of Caragana korshinskii. and the average recognition rate was 80.97%.
机译:为了满足锦鸡儿扦插后留茬的农艺要求。分析了锦鸡儿和枯草、绿草、天空、树枝等背景噪声在不同颜色空间中的颜色特征。确定了利用柠条特征值与背景差异较大的RGB颜色模型对图像进行处理。通过提取柠条特征值与背景噪声差异较大的R值分量和G值分量,对图像进行灰度化处理,并采用加权平均法对图像进行灰度化处理。通过比较,确定采用提取G值分量的灰度化方法,分割效果较好。直方图均衡化的使用使得图像灰度分布均匀,减少了光线对图像亮度的影响。确定了图像二值化的最佳阈值,并用中值滤波器消除椒盐噪声。在图像上执行腐蚀、去除小面积、膨胀和其他操作,并消除和填充主茎上的树枝和凹陷。利用最小二乘法和多元拟合函数,实现了锦鸡儿主茎的修复和拟合。采用阈值分割算法对锦鸡儿主茎进行了识别。平均识别率为80.97%。

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