An Improved ORB Image Feature Matching Algorithm Based on SURF

摘要

This paper proposes an image matching algorithm (L-SURB algorithm) based on the SURF algorithm and the ORB algorithm. The process of algorithm can be divided into four steps. Firstly, the image is enhanced by Laplacian operator. Secondly SURF detector is used to detect feature points. Thirdly, the ORB descriptor is used to describe the feature points to generate a rotation invariant binary descriptor. Finally, the rough matching of the feature points is completed by Hamming distance and the exact matching is realized by Lowe's algorithm. The results of experiment show that L-SURB algorithm effectively solves the problem that ORB algorithm is sensitive to image brightness and lacking in scale invariance, which greatly improves the matching accuracy. At the same time, the matching speed of L-SURB algorithm is increased by 81.5% compared with SURF algorithm.