@conference {13188,
	title = {Detecting rotational symmetries},
	booktitle = {Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on},
	volume = {2},
	year = {2005},
	month = {2005/10//},
	pages = {954 - 961 Vol. 2 - 954 - 961 Vol. 2},
	abstract = {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</sub> 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.},
	keywords = {axial, computational, detection;, field;, flow;, geometry;, gradient, graph, graph;, image, image;, magnitude, methods;, multiple, n-sided, object, polygons;, recognition;, rotational, symmetries;, symmetry;, theory;, tire, tyres;, vector},
	doi = {10.1109/ICCV.2005.71},
	author = {Shiv Naga Prasad,V. and Davis, Larry S.}
}
