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Many vision tasks rely upon the identification of sets of corresponding features among different images. In this paper, we proposed a new feature-matching algorithm only based on geometric constraints rather than scene-dependent constraints. Through four novel schemes, homography is successfully used to iteratively remove the ambiguity of correspondences that are produced by epipolar geometry, even for curved scenes that are of high depth variations and content complexities. Our experiment results show that the proposed method is effective and robust.