A Fast SIFT Feature Matching Algorithm for Image Registration
Kun Li, Shangbo Zhou · 2011
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 Emax) in a single k-d tree. In order to get the relationships among the number of SIFT features, Emaxand 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 Emaxcan 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.