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Image Matching Based on Dual and Graph Transformation Matching

Z.l Hossein-Nejad, N. Parhizgar


Image matching is an essential step in many image processing applications such as registration, mosaicking. Scale invariant feature transform (SIFT) is one of the most applicable and powerful methods proposed in the last decade for image matching that In this paper, double matching is used to increase matching precision in SIFT algorithm. Although dual matching in the SIFT algorithm has a very good performance, this method is not suitable for matching images with identical patterns. In this paper, using dual matching in SIFT algorithm and integrating it with graph transformation matching (GTM) algorithm, we have offered a new and efficient method to improve matching performance in images with duplicated patterns. Simulation results confirm the superiority of the proposed methods in comparison with SIFT and RANSAC in terms of and precision of matching, SITMMC and SITMMR.


Image Matching, False matches, Scale Invariant Feature Transform (SIFT) algorithm

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