基于图像的玉米叶倾角提取算法与应用研究

Extraction and Application of Maize Leaf Inclination Angle Using Digital Images

叶倾角是玉米冠层的重要特征,群体合理的叶倾角分布,对提高光能利用率和生产潜力有重要意义。基于灰度化、直方图均衡化、中值滤波、Otsu分割、形态学操作、连通区识别和骨架化等数字图像处理技术,提出使用Freeman链码识别植株茎叶连接点,进而提取玉米叶倾角的算法。结果表明,Freeman链码对叶尖点识别率为94.47%,对茎叶连接点的识别率为93.94%,叶倾角的实测值与计算值的相关系数r=0.94,实现了叶倾角的高效、准确提取。玉米叶倾角表现为随着叶位的降低而降低,不同层位叶倾角随着归一化植被指数(NDVI)的增大而增大。

Leaf inclination angle is one of the major features of maize population canopy.The rational distribution of leaf inclination angles is of great importance in light use efficiency and production potential.After digital image processing,including gray‑scale,histogram equalization,median filter,Otsu segmentation,morphological operation,connectivity identification and skeletonization,Freeman codes were used to identify maize stem leaf joints and then leaf inclination angles were extracted.Leaf apex and joints were correctly identified by 94.47% and 93.94%,respectively.The correlation coefficient between observations and calculations of leaf inclination angle was 0.94.This method showed high efficiency and accuracy in leaf inclination angle extraction.Maize leaf inclination angle decreased with the lowering of leaf positions,and increased with the growth of NDVI.The quick and precise extraction of leaf inclination angle will provide scientific basis for phenotype retrieval,growth and development monitoring and agricultural resource use.