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Development of uncut crop edge detection system based on laser rangefinder for combine harvesters 被引量:7
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作者 Zhao Teng Noboru Noguchi +2 位作者 Yang Liangliang Kazunobu Ishii Chen Jun 《International Journal of Agricultural and Biological Engineering》 SCIE EI CAS 2016年第2期21-28,共8页
The objective of this research was to develop an uncut crop edge detection system for a combine harvester.A laser rangefinder(LF)was selected as a primary sensor,combined with a pan-tilt unit(PTU)and an inertial measu... The objective of this research was to develop an uncut crop edge detection system for a combine harvester.A laser rangefinder(LF)was selected as a primary sensor,combined with a pan-tilt unit(PTU)and an inertial measurement unit(IMU).Three-dimensional field information can be obtained when the PTU rotates the laser rangefinder in the vertical plane.A field profile was modeled by analyzing range data.Otsu’s method was used to detect the crop edge position on each scanning profile,and the least squares method was applied to fit the uncut crop edge.Fundamental performance of the system was first evaluated under laboratory conditions.Then,validation experiments were conducted under both static and dynamic conditions in a wheat field during harvesting season.To verify the error of the detection system,the real position of the edge was measured by GPS for accuracy evaluation.The results showed an average lateral error of±12 cm,with a Root-Mean-Square Error(RMSE)of 3.01 cm for the static test,and an average lateral error of±25 cm,with an RMSE of 10.15 cm for the dynamic test.The proposed laser rangefinder-based uncut crop edge detection system exhibited a satisfactory performance for edge detection under different conditions in the field,and can provide reliable information for further study. 展开更多
关键词 laser rangefinder technology crop edge detection combine harvester NAVIGATION field profile modeling
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基于视觉识别的小麦收获作业线快速获取方法 被引量:22
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作者 赵腾 野口伸 +2 位作者 杨亮亮 石井一畅 陈军 《农业机械学报》 EI CAS CSCD 北大核心 2016年第11期32-37,共6页
针对小麦生长分布不均等情况下激光作业线检测系统精度偏低的问题,提出了基于视觉的小麦收获作业线快速获取的方法。通过对成熟期麦田的彩色图像进行对比度增强和降低亮度的处理,将其转换为灰度图像,利用阈值分割方法分离已收获与待收... 针对小麦生长分布不均等情况下激光作业线检测系统精度偏低的问题,提出了基于视觉的小麦收获作业线快速获取的方法。通过对成熟期麦田的彩色图像进行对比度增强和降低亮度的处理,将其转换为灰度图像,利用阈值分割方法分离已收获与待收获区域,对二值图像采用互相关函数法检测已收获与待收获区域的分界点,利用Hough变换法拟合目标直线。所提方法在激光作业线识别系统的基础上扩大了视野范围,并限制了图像处理的范围,试验结果表明该方法对小麦收获作业线的检测结果平均偏差为2.35 cm,标准差为3.26,能够满足小麦收获导航线识别的要求,是一种有效的检测算法。 展开更多
关键词 小麦 收获 视觉识别 导航线 激光作业线识别系统 互相关函数法
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