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Communication Dans Un Congrès Année : 2007

Selective Image Diffusion for Oriented Pattern Extraction

Résumé

Anisotropic regularization PDE's (Partial Differential Equation) raised a strong interest in the field of image processing. The benefit of PDE-based regularization methods lies in the ability to smooth data in a nonlinear way, allowing the preservation of important image features (contours, corners or other discontinuities). In this article, a selective diffusion approach based on the framework of Extreme Physical Information theory is presented. It is shown that this particular framework leads to a particular regularization PDE which makes it possible integration of prior knowledge within diffusion scheme. As a proof a feasibility, results of oriented pattern extractions are presented on ad hoc images. This approach may find applicability in vision in robotics.
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Dates et versions

hal-00377679 , version 1 (22-04-2009)

Identifiants

  • HAL Id : hal-00377679 , version 1

Citer

Aymeric Histace, Vincent Courboulay, Michel Ménard. Selective Image Diffusion for Oriented Pattern Extraction. ICINCO'07, May 2007, Angers, France. pp.270-274. ⟨hal-00377679⟩
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