Identification of early crop row for drillcrops based on reverse perspective transformation
1. Beijing Research Center for Intelligent Equipment Technology in Agricultural, Beijing 100097, China; 2. National Engineering Research Center Information Technology in Agricultural, Beijing 100097, China; 3. School of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo, Shandong 255000, China; 4. Xinjiang Agriculture Academy, Shihezi, Xinjiang 832000, China
Abstract：To meet the requirements of field working along the drill crops, a new crop row detection method was proposed. The camera was installed in front of the tractor to obtain the relative space position of farm implements or crop rows. To improve the recognition accuracy of crop rows, the inverse perspective transformation algorithm was used to eliminate the image geometric distortion, and the ossification algorithm was used to obtain the intersection of the skeleton lines of crop rows in the reverse perspective image. The bottom area of the perspective image was selected for vertical projection, and the edge points of the crop rows in the perspective image were obtained. The inverse perspective transformation was carried out, and the intersection points of skeleton lines were divided in the inverse perspective image according to the edge points. The results of identifying and fitting 300 wheat rows with different growth conditions show that the average error of crop row fitting is 2.136 7 degree with standard deviation of 1.024 3 degree and average time consuming of 0.364 7 s, which can meet the real-time requirements.
赵学观1,2, 马伟1,2, 高原源1, 臧云飞3, 何义川4, 王秀1,2. 基于逆透视变换的条播作物早期作物行识别[J]. 江苏大学学报（自然科学版）, 2019, 40(6): 668-675.
ZHAO Xueguan1,2, MA Wei1,2, GAO Yuanyuan1, ZANG Yunfei3, HE Yichuan4, WANG Xiu1,2. Identification of early crop row for drillcrops based on reverse perspective transformation[J]. Journal of Jiangsu University(Natural Science Eidtion)
, 2019, 40(6): 668-675.
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2019, Vol. 40 
