Abstract: In response to the challenges of labor-intensive and time-consuming manual aquatic plant cleaning in crab farming, a method for image-guided navigation line fitting of water grass in crab ponds is proposed. The proposed approach involves several steps. First, RGB images of aquatic plants are read and converted into HSV color space. The H component is selected for binary segmentation, and the segmented image is then filled. Secondly, based on the differences in the water grass image area, parameters are set to delete the small area parts, and the processed image is processed by morphology to retain the target area. Then, the midpoint of non-zero pixels in the binary image is searched by column to obtain the morphological characteristic curve of the aquatic plant image. Finally, based on the characteristic curve, the navigation line is fitted using the least square method. The experimental results show that the relative error of the fitted navigation line is within 0.498%. The average absolute value of the relative error is 0.247%. The average processing time is 0.005 s. The method proposed in this paper shows good accuracy and real-time performance in fitting navigation lines for aquatic plant images, which can lay a theoretical and technical foundation for the development of visually guided aquatic plant cleaning workboats.