|Author(s)||Chauris H.1, 2, Karoui Imen1, 3, Garreau Pierre3, 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|
|WOS© Times Cited||15|
|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.|
Chauris H., Karoui Imen, Garreau Pierre, Wackernagel H., Craneguy Philippe, Bertino L. (2011). The circlet transform: A robust tool for detecting features with circular shapes. Computers & Geosciences, 37(3), 331-342. Publisher's official version : https://doi.org/10.1016/j.cageo.2010.05.009 , Open Access version : https://archimer.ifremer.fr/doc/00033/14451/