The circlet transform: A robust tool for detecting features with circular shapes |
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Authors: | H Chauris I Karoui P GarreauH Wackernagel P CraneguyL Bertino |
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Affiliation: | a Centre de Géosciences, Mines ParisTech, 35 rue Saint-Honoré, 77300 Fontainebleau, France b UMR-Sisyphe 7619, UPMC, Paris, France c Ifremer, Plouzané, France d Actimar, Brest, France e Nersc, Bergen, Norway |
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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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Keywords: | Circlet transform Circle detection Image processing Multi-scale representation Computer vision |
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