We present an algorithm for detecting multiple rotational symmetries in natural images. Given an image, its gradient magnitude field is computed, and information from the gradients is spread using a diffusion process in the form of a gradient vector flow (GVF) field. We construct a graph whose nodes correspond to pixels in tire image, connecting points that are likely to be rotated versions of one another The n-cycles present in tire graph are made to vote for C/sub n/ symmetries, their votes being weighted by the errors in transformation between GVF in the neighborhood of the voting points, and the irregularity of the n-sided polygons formed by the voters. The votes are accumulated at tire centroids of possible rotational symmetries, generating a confidence map for each order of symmetry. We tested the method with several natural images.
Detecting rotational symmetries
Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 ; 2 ; 954-961 Vol. 2
2005-01-01
695392 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Detecting Rotational Symmetries
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