A survey of image registration techniques
ACM Computing Surveys (CSUR)
Design of Multiparameter Steerable Functions Using Cascade Basis Reduction
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Overview of Medical Image Registration
ICCIMA '03 Proceedings of the 5th International Conference on Computational Intelligence and Multimedia Applications
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In this paper, we derive a technique for analysis of local distortions which affect data in real-world applications. In the paper, we focus on image data, specifically handwritten characters. Given a reference image and a distorted copy of it, the method is able to efficiently determine the rotations, translations, scaling, and any other distortions that have been applied. Because the method is robust, it is also able to estimate distortions for two unrelated images, thus determining the distortions that would be required to cause the two images to resemble each other. The approach is based on a polynomial series expansion using matrix powers of linear transformation matrices. The technique has applications in pattern recognition in the presence of distortions.