%0 Conference Paper
%B Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on
%D 2005
%T Detecting rotational symmetries
%A Shiv Naga Prasad,V.
%A Davis, Larry S.
%K axial
%K computational
%K detection;
%K field;
%K flow;
%K geometry;
%K gradient
%K graph
%K graph;
%K image
%K image;
%K magnitude
%K methods;
%K multiple
%K n-sided
%K object
%K polygons;
%K recognition;
%K rotational
%K symmetries;
%K symmetry;
%K theory;
%K tire
%K tyres;
%K vector
%X 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_{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.
%B Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on
%V 2
%P 954 - 961 Vol. 2 - 954 - 961 Vol. 2
%8 2005/10//
%G eng
%R 10.1109/ICCV.2005.71