基于机器视觉的玉米叶片表型参数定量方法研究

W. Jinyong, Tan Wenrong, Hou Shuaimin, Wang Yang, Zhang Hongna
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引用次数: 2

摘要

本文旨在建立一种自动准确监测玉米生长的模型(方法)。应用最新的计算机视觉技术计算提取表面特征参数的方法。采用双目视觉技术对玉米图像进行三维点云计算。同时,利用双边滤波建立的三维点降噪,建立玉米三维重建模型。在三维模型中,玉米的高度和宽度按比例计算。该方法的误差率为0.52%。为玉米的生长监测和虚拟生长提供参考。
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Research on Quantification Method of Maize Leaf Phenotype Parameters Based on Machine Vision
This paper aims to obtain a model (method) for monitering the growth of corn automatically and accurately. The latest computer vision technology is applied to calculate the method of extracting the surface characteristic parameters. Binocular vision technology is used to calculate the 3D point cloud of maize image. Meanwhile, the 3D point noise reduction established by bilateral filtering is adopted to establish the 3D reconstruction model of maize. In the 3D model, the height and width of maize are calculated proportionally. The error rate of the proposed method is 0.52%. This work provides a reference for the growth monitoring and virtual growth of corn.
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