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<title>Plant species identification, size, and enumeration using machine vision techniques on near-binary images</title>

光栅图形 圆度(物体) 形状分析(程序分析) 周长 人工智能 机器视觉 计算机科学 植物种类 叶大小 数学 植物 生物 生物系统 几何学 生态学 静态分析
作者
D. M. Woebbecke,George E. Meyer,K. Von Bargen,David A. Mortensen
出处
期刊:Proceedings of SPIE 被引量:127
标识
DOI:10.1117/12.144030
摘要

Shape parameters such as aspect, roundness, and the ratio of thickness to perimeter were used to describe plant shape and are different according to the species that they represent. Color slide images of several species of plants were digitized for computer analysis. Three optical methods were tested to separate target plants from the soil and residue background. The separation method that provided the best contrast was the normalized difference index. Subtracting the blue or the red raster from the green raster also provided good separation on soils with little residue. Once the plant image had been isolated from the background, leaf edges were automatically traced using a commercial software package. Analysis of the shape of the plant outline was then performed, resulting in the plant shape parameters. Grasses and broadleaf plants had similar values for each shape parameter during the first ten days after emergence. After this period, differences occurred between grasses and broadleaf plants. The parameter that best discriminated grasses from broadleaf plants was the aspect (major axis length/minor axis length). However, when a grass sends out more than one shoot radially from the stem, the aspect will be similar to broadleaf plants. This study contributes to the design of a system that can determine weed populations and identify plant species without the use of human intervention.
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