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首页> 外文会议>Machine Vision Applications in Industrial Inspection XIV; Electronic Imaging Science and Technology >Development of methods based on double Hough Transform or Gabor filtering to discriminate between crop and weed in agronomic images
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Development of methods based on double Hough Transform or Gabor filtering to discriminate between crop and weed in agronomic images

机译：基于双霍夫变换或Gabor滤波的方法的开发，以在农艺图像中区分农作物和杂草

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This paper presents two spatial methods to discriminate between crop and weeds. The application is related to agronomic image with perspective crop rows. The first method uses a double Hough Transform permitting a detection of crop rows and a classification between crop and weeds. The second method is based on Gabor filtering, a band pass filter. The parameters of this filter are detected from a Fast Fourier Transform of the image. For each method, a weed infestation rate is obtained. The two methods are compared and a discussion concludes about the abilities of these methods to detect the crop rows in agronomic images. Finally, we discuss this method regarding the capability of the spatial approach for classifying weeds from crop.
机译：本文提出了两种区分作物和杂草的空间方法。该应用程序涉及带有农作物透视图的农艺图像。第一种方法使用双重霍夫变换，可以检测农作物行并在农作物和杂草之间进行分类。第二种方法基于Gabor滤波（带通滤波器）。该滤波器的参数是从图像的快速傅立叶变换中检测到的。对于每种方法，均获得了杂草侵染率。比较了这两种方法，并讨论了这些方法检测农艺图像中农作物行的能力。最后，我们讨论了有关空间方法对农作物杂草进行分类的方法。

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