| 基于激光视觉的温室作物茎叶量测方法 |
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| 引用本文： | 张 瑜,汪小旵,孙国祥,李永博,孙 鑫.基于激光视觉的温室作物茎叶量测方法[J].农业机械学报,2014,45(9):254-259. |
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| 作者姓名： | 张 瑜 汪小旵 孙国祥 李永博 孙 鑫 |
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| 作者单位： | 南京农业大学;南京农业大学;江苏省现代设施农业技术与装备工程实验室;江苏省现代设施农业技术与装备工程实验室;南京农业大学 |
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| 基金项目： | 国家自然科学基金资助项目（61273227） |
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| 摘 要： | 为实时获取温室作物生长形态参数,应用线激光,对作物整体进行非接触式扫描,通过CCD摄像机实时拍摄扫描过程,采用重心法计算激光光条中心,获取作物叶片与茎秆的三维点云信息,实现作物形态三维点云结构重建;提出适用于作物三维点云数据特征的迭代法,提取叶片点云子集的中心轴线,通过曲线拟合计算叶片长度;根据摄像机透视原理,提出针对细小茎秆的静态定位法计算茎秆直径。试验表明,激光视觉量测叶片长度与茎秆直径的准确率分别为95.39%(SE为0.2961,R2=0.916)和94.55%(SE为0.008 7,R2=0.915)。
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| 关 键 词： | 温室 作物茎叶 形态参数 激光视觉 三维点云 |
| 收稿时间： | 2014/4/15 0:00:00 |
Leaves and Stems Measurement of Plants Based on Laser Vision in Greenhouses |
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| Zhang Yu,Wang Xiaochan,Sun Guoxiang,Li Yongbo and Sun Xin.Leaves and Stems Measurement of Plants Based on Laser Vision in Greenhouses[J].Transactions of the Chinese Society of Agricultural Machinery,2014,45(9):254-259. |
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| Authors: | Zhang Yu Wang Xiaochan Sun Guoxiang Li Yongbo and Sun Xin |
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| Institution: | Nanjing Agricultural University;Nanjing Agricultural University;Jiangsu Province Engineering Laboratory for Modern Facilities Agricultural Technology and Equipment;Jiangsu Province Engineering Laboratory for Modern Facilities Agricultural Technology and Equipment;Nanjing Agricultural University |
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| Abstract: | A laser vision based measurement system consisting of a camera and a laser sheet that scanned the plant vertically was developed to measure the stem diameters and leaf lengths automatically. The 3D point cloud was obtained with the laser sheet scanning the plant vertically, while the camera videoed the process of laser scanning. Laser line centers were extracted by improved centroid method. The 3D point cloud structure of the sample plant was obtained. For leaf length measurement, iteration method for point clouds was used to extract the axis of the leaf point cloud set. The centroid of the subset of points was calculated and taken as the next axis point. Leaf length was calculated by curve fitting on these axis points. In order to increase the accuracy of curve fitting, bi-directional starting point selection was used. To evaluate the method in a sample of 8 water spinaches, the lengths of leaves and diameters of stems were measured manually and plotted versus their automatically measured counterparts. The accuracy of leaf lengths and stem diameters are 95.39% and 94.55% respectively. The tests proved that laser vision based method could be used on plant geometries measurement in greenhouses costly and portably. |
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| Keywords: | Greenhouse Leaf and stem of plant Morphological parameters Laser vision 3D point clouds |
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