An efficient image matching method using Speed Up Robust Features

The kernel of stereo vision system is stereo matching. In this paper proposed, an efficient image matching algorithm based on Speed Up Robust Features (SURF). Compared with traditional methods, this approach has enormous advantages of less computations and short time-consuming. The approach uses SURF algorithm to extract feature points. The feature descriptor of the approach is determined by Haar wavelet. The RANdom SAmple Consensus (RANSAC) algorithm is used to eliminate the false matches and wrong match point. The experimental results show that the approach is robust and has fast matching speed. That makes an important application field of 3D reconstruction.