Singular-Value-Decomposition Based Scale Invariant Image Matching

In this paper, an image matching algorithm combining a SVD matching approach and scale invariant measure is proposed to relate images with large-scale variations. To obtain a better performance on handling redundant points, we modify the SVD matching approach which enforces the condition of minimal distance between the structures of point patterns at the same time ensures the likeliness of the matched points. Together with the adoption of scale invariant features, the proposed method can match features undergoing significant scale changes and provide a set of matches containing a high percentage of correct matches without any statistical outlier detection.