Features Image Matching Approach Based on SIFT and RANSAC

In order to improve the ability of antiinterference in the matching of image feature, a new matching method is proposed based on SIFT and RANSAC. Firstly, using SIFT to extract invariant features from images, best bin first research to be performed and computer the Euclidean distance ratio of nearest neighbor feature vector and second nearest neighbor feature vector to achieve the prematching. After that, RANSAC robust estimation is performed to eliminate the wrong feature matching. Finally, transformation parameters between matching and template image is computed by reliable matching points. The experimental results indicate that the matching algorithm is invariant to scale and rotation，and a substantial range of affine distortion, addition of noise, and can effectively complete the object matching between images.