Aiming at the problems of high mismatching rate and poor robustness of the ORB matching algorithm, an improved ORB-LBP feature matching algorithm based on fusion descriptors is proposed.First of all, the algorithm constructs the pyramid scale space for the input image, detects the oFAST key points on each layer to improve the scale invariance of the algorithm.Then, the image block is used instead of the pixel to improve the anti-noise performance of the LBP algorithm, and the minimum value selecting and sorting are used to make its rotation invariant.Finally, in the process of generating rBRIEF-LBP descriptor, the 128-bit modified LBP descriptor is used instead of the last 128-bit of the rBRIEF descriptor with low variance, to make full use of the image information and improve the matching accuracy and robustness.The experimental results show that, the proposed algorithm has much better matching accuracy and robustness in the case of scale changing, rotating and brightness changing than the traditional ORB does, which can better satisfy the requirements of fast and accurate matching of complex images.