The circlet transform: A robust tool for detecting features with circular shapes

Type Publication
Date 2011-03
Language English
Copyright 2010 Elsevier Ltd All rights reserved.
Author(s) Chauris H.1, 2, Karoui Imen1, 3, Garreau PierreORCID3, Wackernagel H.1, Craneguy Philippe4, Bertino L.5
Affiliation(s) 1 : Mines ParisTech, Ctr Geosci, F-77300 Fontainebleau, France.
2 : UPMC, UMR Sisyphe 7619, Paris, France.
3 : IFREMER, Plouzane, France.
4 : Actimar, Brest, France.
5 : Nersc, Bergen, Norway.
Source Computers & Geosciences (0098-3004) (Pergamon-elsevier Science Ltd), 2011-03 , Vol. 37 , N. 3 , P. 331-342
DOI 10.1016/j.cageo.2010.05.009
WOS© Times Cited 9
Keyword(s) Circlet transform, Circle detection, Image processing, Multi-scale representation, Computer vision
Abstract We present a novel method for detecting circles on digital images. This transform is called the circlet transform and can be seen as an extension of classical 1D wavelets to 2D; each basic element is a circle convolved by a 1D oscillating function. In comparison with other circle-detector methods, mainly the Hough transform, the circlet transform takes into account the finite frequency aspect of the data; a circular shape is not restricted to a circle but has a certain width. The transform operates directly on image gradient and does not need further binary segmentation. The implementation is efficient as it consists of a few fast Fourier transforms. The circlet transform is coupled with a soft-thresholding process and applied to a series of real images from different fields: ophthalmology, astronomy and oceanography. The results show the effectiveness of the method to deal with real images with blurry edges.
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