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玉米长势是指玉米生长的状况与趋势,在生长期内实时掌握长势是玉米生产调控的关键,玉米长势可以通过叶面积、叶尖距、叶基角等特征参数来衡量。吉林省是我国主要的玉米种植区域,种植规模多为小地块,如果采用传统人工方式测量玉米长势,需要耗费大量人力、物力,而遥感技术适用于大面积种植,因此采用人工测量与遥感技术都具有明显的局限性。该研究采用数字图像处理技术,利用固定影像采集设备获取不同生长期玉米多尺度影像,首先利用灰度化和增强技术对影像进行前期预处理,然后使用迭代阈值分割算法提取影像中玉米植株区域,通过图像细化技术并结合参照物标定方法获取玉米植株的株高、叶尖距、叶基角和冠层面积等特征参数,最后对获取的特征参数使用回归分析建立玉米长势模型。试验结果证明,提出的方法有效可行,可以作为人工测量和遥感技术必要有益的补充。
Maize growth refers to the status and trends of corn growth. It is the key to control maize production in real time during growing season. Maize growth can be measured by the characteristic parameters of leaf area, tip distance and leaf base angle. Jilin Province is the main maize planting area in our country. The planting scale is mostly small plots. If the traditional artificial way to measure the maize growth takes a lot of manpower and material resources, and the remote sensing technology is suitable for large-scale planting, the artificial measurement and remote sensing technology All have obvious limitations. In this study, digital image processing technology was used to acquire multi-scale images of corn at different growth stages using a fixed image acquisition device. First, the image was preprocessed by using the gray-level and enhancement techniques. Then, the image of corn plants was extracted by iterative threshold segmentation algorithm. The characteristics of plant height, tip distance, leaf base angle and canopy area of maize plants were obtained by image thinning technique and reference standard calibration method. Finally, the regression model was established by using regression analysis of the acquired characteristic parameters. The experimental results show that the proposed method is effective and feasible and can be used as a useful supplement to the manual measurement and remote sensing technology.