In view of the large similarity between the weight limit sign and the speed limit sign, which is easy to cause false detection and other problems, combining the two-dimensional OTSU automatic threshold segmentation method with strong anti-noise ability and the Jumping Spider Optimization Algorithm (JSOA) with strong searching ability, a two-dimensional OTSU weight limit sign recognition algorithm based on improved JSOA is proposesd. The algorithm counted the two-dimensional gray histogram of region of interest of traffic signs, solved the threshold of segmentation of two-dimensional OTSU using the improved jumping spider algorithm, quickly realized the binarization of traffic sign images, used DBSCAN to cluster the edge points of the binarization image, and finally correctly identified the weight limit sign according to the relative position of the clustering results. The experimental results show that the operation time is reduced by 34.16% without reducing the recognition rate, and the weight limit sign and speed limit sign can be correctly distinguished.