Image Feature Matching Method of High-Speed Railway Catenary with Improved AKAZE Algorithm

Aiming at the problem that the traditional multi-scale feature matching algorithm is difficult to maintain the image local accuracy and edge details in the process of high-speed railway catenary image matching detection, an improved accelerated nonlinear diffusion (AKAZE) algorithm for high-speed railway catenary image feature matching is proposed. Firstly, the method of edge feature and local binary pattern texture feature fusion is used to overcome the shortage of feature points in traditional catenary image. Then, the improved AKAZE algorithm is used to extract the features of catenary image, and the binary robust independent elementary feature (BRIEF) descriptor is proposed to describe the feature points. Next, the false matching points are eliminated by fast similar neighborhood search and random sampling consistent algorithm. Finally, the image difference method is used to realize the matching detection of catenary image. Experimental results show that, compared with the AKAZE feature matching algorithm, the average matching accuracy of the proposed algorithm is improved by 22. 16%, and the operation efficiency of the algorithm is also greatly improved.