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基于模糊理论的树冠图像边缘检测算法研究 被引量:1

Research on Canopy Image Edge Detection Algorithm Based on Fuzzy Theory
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摘要 介绍了一种变量施药的靶标识别方法,采用T-S模糊模型,根据绿色植物和背景颜色的特征值(R、G、B)差异性,采用超绿指标[Excess green,ExG]来区别靶标与背景的隶属度,定义了噪声和边缘隶属度函数,根据模糊推理结果,对植物叶片图像去除噪声后再进行边缘检测,可有效检测图像边缘。降低算法的复杂度,提高了效率,在抗噪性能方面能有效地避免噪声的干扰、节约时间、运算速度快。 This paper introduced a method for target recognition in variable pesticide application. Based on T-S fuzzy model, according to the differences in color eigenvalues( R,G,B)between green plant and its background,this study used excess green ( ExG)indicators to distinguish the membership degree of the target and its background,and defined the membership functions of the noise and the edge. According to the results of fuzzy inference,this article conducted the edge detection of plant leaf image after removing the noise,which could effectively detect the image edge. This method reduced the complexity of the algorithm,improved the working efficiency due to less working time and high operating rate,and could effectively avoid the interference of the noise.
出处 《江西农业学报》 CAS 2014年第8期109-113,共5页 Acta Agriculturae Jiangxi
基金 国家"863"计划"果园精准生产技术与装备"(2012AA101904)
关键词 图像处理 模糊理论 边缘检测 ExG Image processing Fuzzy theory Edge detection ExG
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