Image Registration Algorithm Based on FAST and SURF
AN Weishen · Jisuanji gongcheng · 2015
For Scale Invariant Feature Transform(SIFT)and Speeded-up Robust Feature(SURF)needing a long time in the corner detecting and feature points matching,an improved image registration algorithm is put forward.A Gaussian scale pyramid of the reference image and the matching image are established.Feature points which have different scale information are detected from each level in the image pyramid.It gets Features from Accelerated Segment Test(FAST)point with different scales.An orientation is assigned to every feature point,and feature vector is calculated by using the same way as SURF.The original matching points which have minimum Euclidean distance under some condition are determined through fast approximate nearest neighbor search.The false matching points are excluded by Randomized Sample Consensus(RANSAC) algorithm,and the transformation matrix is gained.Experimental results show that the algorithm is better than SURF and SIFT in feature detection speed and matching speed,and matching accuracy is higher.