To overcome the shortcomings of descriptor BRIEF which is sensitive to image rotation, this paper proposes a improved descriptor RIBRIEF which has the advantages of good identification ability, high descriptor extraction speed, less memory usage, strong robustness and rotation invariant. The study shows that real-time performance of image matching algorithm is largely decided by the number of feature points, the search times of matching points and the computational complexity of descriptor similarity. It therefore proposes optimization algorithms to improve real-time performance of image matching by combining descriptor index and descriptor cluster, applying FAST to stable feature point extraction and calculating descriptor similarity with logic operations. Compared with SURF and BRIEF, experimental results show that RIBRIEF has better performance in robustness and real-time.