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Wheat Rows Detection Based on Machine Vision
Changdong Ma,Hongtu Zhao,Xiaojie Wang 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.9
This study describes a new method for wheat rows detection at the middle growth stage based on Machine Vision. The algorithm includes three steps: (i) vegetation segmentation, (ii) centers points extraction and (iii) wheat rows detection. In the first step, color images were transformed into gray-level images and Otsu’s method was used to implement binarization. Based on the fact that the corresponding center points on two adjacent horizontal scanning lines can’t have a large deviation, in the second step, we firstly extracted the initial center points on the first scanning line based on a sliding window, and then gave a small shift based on positions of the initial center points which have been extracted on the previous scanning line to extract the center points for the next scanning line. Finally, the Randomized Hough transform (RHT) method was employed to locate the wheat rows. Test results indicate that the proposed method can effectively detect the wheat rows at the middle growth stage.
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