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Similarity measures based on correlation have been used extensively for matching tasks. However, traditional correlation-based image matching methods are sensitive to rotation and scale changes. This paper presents a fast correlation-based method for matching two images with large rotation and significant scale changes. Multiscale oriented corner correlation (MOCC) is used to evaluate the degree of similarity between the feature points. The method is rotation invariant and capable of matching image pairs with scale changes up to a factor of 7.Moreover, MOCC is much faster in comparison with the state-of-the-art matching methods. Experimental results on real images show the robustness and effectiveness of the proposed method.

MOCC: A Fast and Robust Correlation-Based Method for Interest Point Matching under Large Scale Changes