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Conference Papers Year : 2015

Texture classification of photographic papers: improving spectral clustering using filterbanks on graphs

Pierre Borgnat
Patrice Abry

Abstract

From the point of view of graph signal processing, we show that spectral clustering is equivalent to an ideal low-pass filterbank. Building upon previous multiscale community detection ideas [11], and integrating the concept of community cores [8], we propose a data-driven filterbank-based classification method. We apply this method to the texture classification of photographic papers useful to art historians, and we show that it provides a richer and more informative description of the data’s structure in clusters.
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Dates and versions

hal-01518069 , version 1 (04-05-2017)

Identifiers

  • HAL Id : hal-01518069 , version 1
  • OATAO : 17033

Cite

Nicolas Tremblay, Stéphane G. Roux, Pierre Borgnat, Patrice Abry, Herwig Wendt, et al.. Texture classification of photographic papers: improving spectral clustering using filterbanks on graphs. 25eme Colloque Groupe de Recherche et d'Etudes du Traitement du Signal et des Images (GRETSI 2015), Sep 2015, Lyon, France. pp. 1-4. ⟨hal-01518069⟩
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