图像时序数字记录技术在玉米物候演化分析中的应用

S. Serafino, Benjamin Cicerchia, Juan P. Mitriatti, Agustín Balmer, Martín Faroppa, C. Russo, Hugo Ramón
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引用次数: 0

摘要

本文拟通过使用机器人平台实现玉米作物田间试验数字遥感图像与时间序列的配准。该平台的导航试验配备了可见光和多光谱光传感器,并使用了配准过程,使我们能够生成不同遗传品种玉米的“堆叠图像”,目的是获得它们的物候特征,并进行比较。除了位移、光照和不同拍摄角度的基本问题外,还有一个缺点,即物体(植物)不相同,在许多情况下也与以前的图像不相似(物候阶段不同)。此外,在室外环境中感知图像的复杂性,特别是在野外的一般条件下(不平坦的道路表面,气候条件)。所提出的算法是多层数字图像数据库生成的一部分,通过其他数字分析和处理技术,可以自动识别和解释不同特征,以确定所研究的不同遗传玉米品种的反应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Digital Recording of Temporal Sequences of Images Applied to the Analysis of the Phenological Evolution of Maize Crops
This paper intends to implement registration of images to temporal sequences of maize crops digitally sensed in field trials through the use of a robotic platform. The navigation of trials of this platform equipped with visible and multispectral light sensors, and the registration processes used allow us to generate "stacks images" by different genetic varieties of maize with the aim of obtaining a phenological characterization of them, and to compare them. In addition to the basic problems of displacement, lighting, and angle of the different captures, there is the drawback that the objects (plants) are not the same and in many cases also not similar to the previous images (different phenological stages). Added to this is the complexity of sensing the images in outdoor environments, and in particular the general conditions in the field (uneven path surface, climatic conditions). The proposed algorithms are part of the generation of multilayer digital image data banks that allow, through other digital analysis and processing techniques, the automated identification and interpretation of different characteristics for the determination of the response of the different genetic varieties of corn that is studied.
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