Precise image matching: A similarity measure approach

Abstract

An algorithm that utilizes the similarity comparison is proposed to get more proper match result, which is easy to implement. SIFT depends on principal direction which will lead to low precision rate when the direction is incorrectly computed. In this paper, similarities are tested by cosine theorem of matched points in some area to find stable matches and exclude mismatches (push) at first. Part of correct matches in excluded points are revived (pull) through stable matches, which are located in cluster sets centered by stable matched points, thus shrink search field and boosting the algorithm. Sum of Square Distance (SSD) measurement function is tested and chosen as similarity function to accomplish the reviving step. Experimental results show that the proposed method exhibits improved performance compared with SIFT and other methods.