New fast local invariant feature algorithm

In order to solve the problem that traditional local invariant descriptors extracted inaccurate main direction and spent too much time in matching vectors, a new method for fast image registration based on RI-LBP algorithm and hybrid spill-tree was proposed. Firstly, stable feature points of template image and image to be matched were extracted by the proposed FAST-Difference Algorithm. Feature vectors were calculated using rotation invariant RI-LBP descriptors. At last feature vector sets were matched using hybrid spill-tree and mismatching points were eliminated by RANSAC. The problem that the main direction couldn't be extracted accurately was conquered because of the rotation invariant of RI-LBP, which means the feature descriptors were more stable. At the same time the feature vectors contain contained 53 dimensions, which are more simple. Spill-tree had better matching efficiency for high-dimensional data because it omitted the process of backtracking. The experiment results indicated that the proposed method cost much less time while retained nearly the same describing performance with SURF and achieved better performance in rotation and illumination changes.