Robust verification for image feature matching based on RANSAC
Yi Liu · Journal of Chongqing University of Posts and Telecommunications · 2010
Error matching points usually lead to an inaccurate transformation from images into poor image registrations.In this paper,a method for verifying accurate matching features was proposed based on random sample consensus(RANSAC),and a robust algorithm for estimating geometric transform matrix between images was presented.Firstly,initial matching features were obtained from the similarity of feature vectors,and then weights could be gained from the gray information around each feature point.In the process of iterative fitting geometric transform matrix using RANSAC,error matches were eliminated by minimization cost function.Finally,precise image registration was achieved.Experimental results show that the algorithm has good noise robustness and ideal image registration.