SIFT Based Image Matching and Its Applications

Image matching is one of the basic tasks in image processing. It is used to find matched points in two or more images captured under different conditions. These matches can be further used to lots of applications such as image registration, image searching, image retrieving and so on. Generally, one matching algorithm has three components. One is feature detector which is used to find some points. These points are also called corner points, interesting points or feature points. The second one is feature descriptor which is used to describe the selected feature. The third part is matching metrics which shows how to use the features found in previous steps to match points. In this thesis we will first introduce some algorithms prior to SIFT feature detection algorithm. Then the SIFT feature detector algorithm used in the thesis is introduced in detail. Some matching algorithms is further introduced to make the SIFT based matching process more robust, such as K-d tree based searching algorithm and some spatial verification algorithm. Finally, some applications based on algorithms introduced above are proposed including image stitching and image classification.