Abstract
Image registration requires a step of detection and matching of primitives. These phases are important to obtain a reliable registration. In this paper, we mainly focus on geometric registration methods which are based on the extraction and matching of distinctives features in images. Several methods such as SIFT, SURF, BRIEF, BRISK, ORB, FREAK and FRIF, are already proposed. In this paper, we present a comparative study of feature detector and descripts methods for registration which can be classified according to their type of descriptor witch can be local classical or binary.
We have presented, through this study, the difference between geometric methods of descriptor leveling as well as points of interest detector used, and which have an influence on the resetting registration results. We can see that each method has weak points as well as strong points. The major difference is the level of invariance to the type of processing and the temporal complexity.