A Fast SIFT Feature Matching Algorithm for Image Registration

In this paper, a novel fast SIFT (Scale Invariant Feature Transform) feature matching algorithm for image registration is presented. Firstly, for fast SIFT feature matching, we propose a method to optimize the priority k-d tree search algorithm by choosing a proper number of leaf nodes examined (denoted as E_max) in a single k-d tree. In order to get the relationships among the number of SIFT features, E_max and the precisions achieved by the priority k-d tree search algorithm in a single k-d tree, the properties of a single k-d tree and that of the priority k-d tree search algorithm are combined. Referring to these relationships, a proper value of E_max can be selected to achieve an approximate precision in fast time. And then, in image registration, in order to improve matching precision, we have designed the bidirectional priority k-d tree search algorithm in this paper. I. e. the priority k-d tree search algorithm is used twice.