基于纹理和位置特征的麦田杂草识别方法

Weed Detection Method in Wheat Field Based on Texture and Position Features

以化学防除适期麦田杂草为研究对象,对利用条播作物的位置和纹理特征识别田间杂草的方法进行了研究。根据条播作物小麦作物行的间距相对固定等位置特征,利用植物像素直方图法确定作物行的中心线和行宽,并识别行间杂草。然后,以作物行中心为基准来选取纹理块,计算量化级数为8级的H颜色空间的共生矩阵,提取5个纹理特征参数,利用K均值聚类法判别分析各块的类别来识别行内杂草。研究结果表明,杂草的正确识别率约为93%,作物的错误识别率约为7%。

Take the weeds in wheat fields as the research object, a method of weed detection by using the texture and position features was studied. According to the position feature of drilled crops that were regularly sown as a constant row space, the pixel-histogram method was used to determine the central line and the width of crop row. As a result, weeds between crop rows were detected. Moreover, the block of texture was selected on the basis of the central line of crop row. The co-occurrence matrixes of the H color space that was quantified 8 levels were computed. Based on that, five texture parameters were extracted. Then, the K-means clustering method was used to recognize weeds within crop rows. The result of research showed that the correct classification of weeds was 93% and the mistake classification of crops was 7%.