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

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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https://hal-mines-paristech.archives-ouvertes.fr/hal-00574554
Contributeur : Pascale Nalon <>
Soumis le : mardi 8 mars 2011 - 12:02:34
Dernière modification le : jeudi 24 septembre 2020 - 16:34:09

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Hervé Chauris, Imen Karoui, Pierre Garreau, Hans Wackernagel, Philippe Craneguy, et al.. The circlet transform: a robust tool for detecting features with circular shapes. Computers & Geosciences, Elsevier, 2011, 37 (3), pp.331-342. ⟨10.1016/j.cageo.2010.05.009⟩. ⟨hal-00574554⟩

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