Measurement of Individual Maize Height Based on RGB-D Camera

被引:2
|
作者
Qiu R. [1 ]
Miao Y. [1 ]
Ji Y. [1 ]
Zhang M. [1 ]
Li H. [2 ]
Liu G. [2 ]
机构
[1] Key Laboratory of Modern Precision Agriculture System Integration Research, Ministry of Education, China Agricultural University, Beijing
[2] Key Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture, China Agricultural University, Beijing
来源
Zhang, Man (cauzm@cau.edu.cn) | 1600年 / Chinese Society of Agricultural Machinery卷 / 48期
关键词
Image recognition; Plant height; Plant phenotyping; Point cloud processing; RGB-D camera;
D O I
10.6041/j.issn.1000-1298.2017.S0.034
中图分类号
学科分类号
摘要
Plant height is an essential phenotype parameter for assessing plant vigor and estimating plant biomass. In order to rapidly measure individual maize plant height, a method based on RGB-D (red, green, blue-depth) camera was proposed in this paper. Color images and depth images of maize at the jointing stage were captured using RGB-D camera in field. First, the color image of maize was processed by graying and binarizing. Then, morphological open operation was conducted within region of interest, and the largest region of maize image was extracted to remove weed and little leaves. Second, the optimized watershed algorithm was applied to the maize gray image and the boundary was generated, then the circle fitting was carried out for the boundary points. After that, the skeletonization operation was conducted for the maize binary image. There were crossing points at the contact points between leaves, and ending points at the end of leaves. The crossing points and ending points were searched and saved, and the distances between the center of the circle and each crossing point were calculated. Only the crossing point that was nearest to the center of circular was chosen as the maize center. Next, the Dijkstra algorithm was used to find the nearest paths between the maize center and each ending point. The color coordinates of the paths were saved and the corresponding point cloud data were generated based on the mapping relationship between color coordinate, depth coordinate and camera coordinate. Third, the differences between neighbor points of every path were calculated to determine the potential measurement points of the target maize and remove the point cloud data belong to non-target maize leaves. All the paths were compared to find the highest point of maize. The histogram statistic method was applied for point cloud data that were around the highest point of maize to extract ground. Finally, the difference between the highest point of maize and ground was calculated to measure individual maize plant height. Samples were tested to verify the aforementioned method, and the results demonstrate that the method proposed in this paper has a good performance in measuring individual maize plant height. The mean errors and root mean square error (RMSE) of measuring plant height were 1.62 cm and 1.86 cm respectively, indicating that the proposed method can be applied to monitoring plant growth. © 2017, Chinese Society of Agricultural Machinery. All right reserved.
引用
收藏
页码:211 / 219
页数:8
相关论文
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