Image Registration and Mosaic Based on Vector Similarity Matching Principle

To resolve the mismatching problem in image registration and image mosaic, this paper proposes an improved feature matching principle based on vector similarity.First, by detecting feature points in scale space, SIFT (Scale Invariant Feature Transformation) vectors, which represent local properties, are computed;the feature points are matched by using vector similarity method and mismatching point couples are further deleted with the application of mutual mapping theory.And then, the transform matrix is calculated by random sample consensus algorithm.Furthermore, it is optimized by Lenvenberg-Marquardt (L-M) algorithm.Finally, through image fusion, image mosaic is realized.The experimental results indicate new principle improves the matching precision.The method can deal with image registration and mosaic with projective transformation.