基于纹理分析的无人机RGB图像植物类型识别

Михаил Германович Катаев, M. Kataev, Мария Дадонова, Maria M. Dadonova
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引用次数: 0

摘要

到目前为止,装有数码相机的无人驾驶飞行器(uav)已经变得司空见惯。结果图像被收集在正射影成像图中,并更多地用于视觉分析。对图像内容的数值分析仍然很不发达。其中一个分析领域是图像中植被的分配和类型的确定。有许多方法可以突出显示图像中的植物,例如纹理、颜色或索引分析。本文的任务是对从无人机获取的图像进行处理,对图像中的植被进行分离,从中选择需要的植物,并基于纹理分析估计该植物在图像中所占的面积。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of Plant Types by RGB Image Received from UAV by Textural Analysis
To date, flying unmanned aerial vehicles (UAVs), with digital cameras on board, have become commonplace. The resulting images are collected in orthophotomaps and more used for visual analysis. A numerical analysis of the content of images is still poorly developed. One of the areas of analysis is the allocation of vegetation in the image and the determination of types. There are many ways to highlight plants in an image, such as texture, color, or index analysis. In this paper, we set the task of processing the image obtained from the UAV, isolating the vegetation in the image, selecting the desired plants from the set, and estimating the area occupied by this plant in the image based on texture analysis.
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