Abstract: In order to solve the problems that straw detection accuracy is easily affected by uneven illumination and that the existing detection methods have poor detection accuracy for straws without images. This paper proposes a method of image line average gray level standard deviation classification and image block variable threshold method. Firstly, the images were classified by calculating the average gray standard deviation of the rows of the images, and the image whose standard deviation is less than the threshold value is judged as no straw mulching. Then the image whose standard deviation is greater than the threshold is divided into several sub blocks, and each sub block is segmented by Otsu algorithm. Finally, all the sub-blocks are recombined and the straw coverage of the target image is calculated by the basic morphological method. The experimental results show that the method greatly reduces the influence of uneven illumination on the detection results. The detection error of uniform straw distribution image is 2.87%, and the detection error of no straw mulching image is 0.45%, which can improve the applicability of the detection method of crop straw coverage rate.