To promote the automatic realization of coaxial tire type discrimination in vehicle safety inspection, a tire pattern image verification algorithm based on siamese network was proposed. The algorithm is oriented to the tire pattern images of small data sets. On the infrastructure of the siamese network, an image preprocessing module of orientation correction is added to realize the alignment of tire patterns and eliminate the obvious orientation difference between tire images. The Gabor Orientation Filters are used in the lowlevel convolutional network of its subnetwork to improve the learning speed of the network on tire pattern texture features and the robustness of tire image recognition with different quality. Experimental results on CIIP_TPID and WTP datasets show that the accuracy of the proposed algorithm is 0926 and 0849 respectively.