Determination of Plant Phenological Cycle From RGB Images

Михаил Германович Катаев, M. Kataev, Кирилл Ёлгин, Kirill Yolgin
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Abstract

Automated visual assessment of the state of the earth and plants, wilting and pests of leaves, plant growth indicators, using technical vision, can be used as a basis in smart (precision) agriculture (SA). This article discusses a brief review of the literature on the use of computer (technical) vision (CV) for analyzing the condition of agricultural fields and plants growing on them. The introduction of vision systems into real agricultural production practice is associated with the development of complex mathematical approaches that must be resistant to a variety of technical and weather changes. It is necessary to overcome image changes caused by atmospheric conditions and daily and seasonal variations in sunlight. An approach is proposed, which is based on an RGB image obtained using a typical digital camera. The results are given on the use of CV systems in solving individual tasks of agricultural production.
利用RGB图像测定植物物候周期
利用技术视觉对土壤和植物的状态、叶片的枯萎和害虫、植物生长指标进行自动视觉评估,可以作为智能(精准)农业(SA)的基础。本文对利用计算机(技术)视觉(CV)分析农田状况和生长在农田上的植物的文献进行了简要的综述。将视觉系统引入实际的农业生产实践与复杂的数学方法的发展有关,这些方法必须能够抵抗各种技术和天气变化。有必要克服由大气条件和日照的日变化和季节变化引起的图像变化。提出了一种基于典型数码相机获得的RGB图像的方法。给出了CV系统在解决农业生产个别任务中的应用结果。
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