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Aiming at the imprecise identification and positioning of crop seedlings and weeds, which would cause the problems of weeding robots unclean weeding, harming seedlings and affecting yield, a multi-stage image recognition method based on skeleton extraction algorithm was proposed, which realized the accurate identification and location of crop stem center through multi-level progressive fusion of different image algorithms. Firstly, the collected color images were converted to HSV color space for background segmentation. Then, the corrosion algorithm was used to corrode the image, which corroded the weed image information to obtain the image information only containing crops. Finally, the Zhang-Suen thinning algorithm was used to extract the skeleton of the crop image, and the skeleton intersection point was calculated and analyzed to identify and locate the center of the crop stem, so as to achieve accurate identification and positioning of crops. Experimental tests were carried out on 100 images collected at seedling stage. The results showed that the accuracy error of identification and positioning of stem center of crop seedlings was less than 12mm. The method presented can accurately identify the seedlings and weeds in real time and accurately locate the seedlings, providing an accurate and reliable method for crop identification and location for realizing the mechanization of agricultural plant protection operations such as weeding in the field.