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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%.