In this paper, the distribution of weeds in winter wheat was obtained by UAV. A model is established by K value clustering and edge detection algorithms. Key images of different flying angle of UAV for farmland weeds were extracted. The research results show that the edge detection algorithm is suitable for UAV image processing. The recognition accuracy of the weeds was more than 90%. The accuracy of the identification of three typical grass conditions is achieved 98.3%. The conclusion of the study is to provide guidance for UAV variable spraying.