Automatic choice of the threshold of a grain filter via Galton-Watson trees. Application to granite cracks detection

Abstract : The goal of this paper is the presentation of a post-processing method allowing to remove impulse noise in binary images, while preserving thin structures. We use a grain filter as in [5]. We propose a method to automatically determine the required threshold using Galton-Watson processes. We present numerical results and a complete analysis on a synthetic image. We end the numerical section considering a specific application to granite samples crack detection: here we deal with X-tomography images that have been binarized via preprocessing techniques and we want to remove residual impulse noise while keeping cracks and micro-cracks structure.
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Journal of Mathematical Imaging and Vision, Springer Verlag, 2018, 6 (1), pp.50-69. 〈https://link.springer.com/article/10.1007/s10851-017-0743-3?wt_mc=Internal.Event.1.SEM.ArticleAuthorOnlineFirst〉
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Contributeur : Maïtine Bergounioux <>
Soumis le : mardi 10 janvier 2017 - 17:22:51
Dernière modification le : jeudi 3 mai 2018 - 15:32:07

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Romain Abraham, Maïtine Bergounioux, Pierre Debs. Automatic choice of the threshold of a grain filter via Galton-Watson trees. Application to granite cracks detection. Journal of Mathematical Imaging and Vision, Springer Verlag, 2018, 6 (1), pp.50-69. 〈https://link.springer.com/article/10.1007/s10851-017-0743-3?wt_mc=Internal.Event.1.SEM.ArticleAuthorOnlineFirst〉. 〈hal-01337551v2〉

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