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基于图像处理技术的杂草特征提取方法研究
引用本文:谈蓉蓉,朱伟兴.基于图像处理技术的杂草特征提取方法研究[J].传感器与微系统,2009,28(2):56-59.
作者姓名:谈蓉蓉  朱伟兴
作者单位:江苏大学,电气信息工程学院,江苏,镇江,212013
基金项目:江苏省现代农业装备与技术重点实验室开放基金 
摘    要:利用计算机视觉技术将杂草从背景中识别出来进行定位喷洒农药已成为精细农业研究的热点。选取颜色空间OHTA中I'2分量作为特征量;利用基于遗传算法的自动阈值选取方法对特征分量巧进行阈值分割初步分离杂草与小麦;通过颜色聚类和形态滤波获得准确的杂草区域。实验结果表明:直接在彩色空间进行分割,可提高彩色图像的分割效果,利用该方法获得的杂草平均正确识别率达到90.47%。

关 键 词:杂草识别  OHTA颜色空间  遗传算法  聚类  形态滤波

Research of weed feature extraction method based on image processing technology
TAN Rong-rong,ZHU Wei-xing.Research of weed feature extraction method based on image processing technology[J].Transducer and Microsystem Technology,2009,28(2):56-59.
Authors:TAN Rong-rong  ZHU Wei-xing
Affiliation:( School of Electrical Engineering, Jiangsu University, Zhenjiang 212013, China)
Abstract:Computer vision technology used to weed identification from background which to spray herbicide in a precise position has become a hot research of precision agriculture.A weed identification method that takes OHTA as color space and I2′as characteristic variant is presented,automatic threshold selection method on the basis of genetic algorithms for the feature component I2′is used to separate weed and wheat preliminarily,and then color clustering and morphological filtering is used to achieve the accurate weed regions.The experiment results show that separating directly in the color space would improve the segmentation effect of color images,and the average correct identification rate reaches 90.47 % using the method proposed before.
Keywords:weed identification  OHTA color space  genetic algorithmic  cluster  morphological filter
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