ZOU Weijie,HUA Shan,XU Zhifu,et al.Study on Estimation Method of Canopy Coverage for Facility Tomato Based on RGB Images[J].Northern Horticulture,2024,(3):41-50.[doi:10.11937/bfyy.20232618]
基于RGB图像的设施番茄冠层覆盖度估算方法研究
- Title:
- Study on Estimation Method of Canopy Coverage for Facility Tomato Based on RGB Images
- 文章编号:
- 1001-0009(2024)03-0041-10
- 分类号:
- S 641.2
- 文献标志码:
- A
- 摘要:
- 以番茄为试材，采用设施实验箱育苗的方式，通过设施环境下桁架搭载可见光（RGB）相机系统获取图像数据，研究了不同植被指数算法分割番茄冠层图像的精度，并实现设施番茄冠层覆盖度提取方法的评估，以期为其他设施作物的冠层覆盖度估算提供方法指导。结果表明：EXG算法、EXGR算法和CIVE算法均可用于估算设施番茄的冠层覆盖度，与真值之间的均方根误差（RMSE）分别为0.049、0.078、0.088，决定系数（R2）分别为0.911、0.845、0.841，不同植被指数分割算法估算的设施番茄冠层覆盖度之间存在差异，与真值图像相比，EXGR算法在定植10 d的图像分割时，分割精度较低，冠层覆盖度估算值偏大，CIVE算法在定植66 d的图像分割时，由于分割过度，导致冠层覆盖度估算值偏小，而EXG算法在各时期的分割精度较高，冠层覆盖度的估算值与真值之间的吻合度最好。这表明EXG算法能够更有效的实现设施番茄的植土分割且估算精度更高。
- Abstract:
- Taking tomato as the test material，the image data was obtained by using a visible light (RGB) camera system mounted on a scaffold under the facility environment，and the accuracy of different vegetation index algorithms for segmenting tomato canopy images was studied.And the evaluation of the method for extracting the canopy coverage of facility tomato was realized，in order to provide method guidance for the estimation of canopy coverage of other facility crops.The results showed that EXG algorithm，EXGR algorithm and CIVE algorithm could well be used to estimate the canopy coverage for facility tomatoes.The root mean square error (RMSE) between estimation value and true value for facility tomato canopy coverage was 0.049 for the EXG algorithm，0.078 for the EXGR algorithm，and 0.088 for the CIVE algorithm.The coefficient of determination (R2) was 0.911，0.845，0.841 for EXG algorithm，EXGR algorithm and CIVE algorithm respectively.The estimation results of canopy coverage for facility tomato were significant different among different vegetation index segmentation algorithms.Compared with the true value image，the EXGR algorithm had low segmentation accuracy，which overestimates the canopy coverage at 10 days after transplanting.Due to over-segmentation，the CIVE algorithm underestimated the canopy coverage at 66 days after transplanting.The EXG algorithm showed a higher segmentation accuracy at all growing stages and the estimated canopy coverage was close to the true value，compared to the other two algorithms.The EXG algorithm could achieve more efficient plant-soil segmentation and more accurate estimation for tomato canopy coverage than the other two algorithms，which provided methodological guidance of canopy coverage for other crops in facility.
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备注/Memo
第一作者简介：邹伟杰（1999-），男，硕士研究生，研究方向为智能制造技术。E-mail：1030138850@qq.com.责任作者：李双伟（1990-），女，博士，助理研究员，现主要从事源尺度的植物功能-结构-环境互作的表型模型等研究工作。E-mail：lishw@zaas.as.cn.基金项目：国家自然科学基金资助项目（32201658）。收稿日期：2023-08-02