Image registration is the vital technology in computer vision. By developing precise image registration algorithm will meaningfully improve the techniques for the problems in computer vision. Registration process does geometrical alteration that aligns point present in one view of an object with similar points in another view of that object or another object .Steps involved in image registration are feature finding, matching of features, image transformation and resampling. Feature finding and matching have vital role in accuracy of the process. In this paper we have used SIFT (Scale Invariant Feature Transform) for the feature detection which is invariant to scaling, rotation and noise. KNN nearest neighbor is used for matching similar points and the other efficient method in reducing miss matches in the proposed algorithm is Random sample consensus method.
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