Based on feature point, image matching has been widely applied in image registration, object recognition and tracking field. Now, two phase feature point matching (i.e., first coarse matching, then precise matching) is the most commonly used method. However, the two phase matching exists two issues, on the one hand, the impact of coarse matching for precise matching is irreversible, that is, the results of coarse matching will determine the optimal precision of precise matching. On the other hand, the post knowledge which can be obtained from precise matching cannot be regarded as feedback information to coarse matching, which can revise mismatching. Hence, the paper proposes a new feature point matching algorithm which is based on iterative correction. In the algorithm, post knowledge of precise matching is regarded as feedback information to coarse matching. The coarse matching can obtain more correct matching pairs and decrease missing correct matching pairs. After much iterations, better matching can be obtained. Experiments show that the proposed algorithm can extract more matching pairs than traditional two phase method and improves the matching stability.