Abstract
Abstract. A rotation invariant image matching algorithm is introduced in this paper. The feature descriptor of feature points is calculated in polar coordinate system which achieves rotation invariant. The Wallis filter and image edge extraction are applied to reduce the influence of noise an light difference. After constructing the image feature vectors, the potential correspondences are found firstly and then the Generalized Hough Transform (GHT) is used to purify the matching result . The experiment results of three data sets show that the method is robust to image rotation, time and space efficient and is sufficient to produce matching points which can be used as initial values for further accurate image matching.
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