A Fast Image Matching Algorithm Based on GPU Parallel Computing

摘要

In process of image matching, Scale Invariant Feature Transform (SIFT) algorithm is one of the best performance algorithms. But the drawback of being complex and time-consuming limits its application in more fields. Aiming at this shortage of SIFT algorithm, this study proposes a fast SIFT algorithm based on Graphic Processing Unit (GPU) and analyzes its parallelism. It is further optimized according to the detailed analysis on the thread and memory model of the graphic hardware. It is experimentally shown that the speed of the proposed algorithm is 25-45 times faster than the original algorithm. Processing 640×480 images, its speed can be up to 24 frames per second. The conclusion is that proposed algorithm can meet the needs of real-time applications.