Skip to Main content Skip to Navigation
Conference papers

Multiscale Anisotropic Texture Unsupervised Clustering for Photographic Paper

Abstract : Texture characterization of photographic papers is likely to provide scholars with valuable information regarding artistic practices. Currently, texture assessment remains mostly based on visual and manual inspections, implying long repetitive tasks prone to inter- and even intra-observer variability. Automated texture characterization and classification procedures are thus important tasks in historical studies of large databases of photographic papers, likely to provide quantitative and reproducible assessments of texture matches. Such procedures may, for instance, produce vital information on photographic prints of uncertain origins. The hyperbolic wavelet transform, because it relies on the use of different dilation factor along the horizontal and vertical axes, permits to construct robust and meaningful multiscale and anisotropic representation of textures. In the present contribution, we explore how unsupervised clustering strategies can be complemented both to assess the significance of extracted clusters and the strength of the contribution of each texture to its associated cluster. Graph based filterbank strategies are notably investigated with the aim to produce small size significant clusters. These tools are illustrated at work on a large database of about 2500 exposed and non exposed photographic papers carefully assembled and documented by the MoMA and P. Messier's foundation. Results are commented and interpreted.
Complete list of metadatas

Cited literature [18 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01511889
Contributor : Open Archive Toulouse Archive Ouverte (oatao) <>
Submitted on : Friday, April 21, 2017 - 5:13:38 PM
Last modification on : Sunday, June 14, 2020 - 3:28:12 AM
Document(s) archivé(s) le : Saturday, July 22, 2017 - 2:21:28 PM

File

roux_17040.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01511889, version 1
  • OATAO : 17040

Citation

Stéphane G. Roux, Nicolas Tremblay, Pierre Borgnat, Patrice Abry, Herwig Wendt, et al.. Multiscale Anisotropic Texture Unsupervised Clustering for Photographic Paper. 7th IEEE International Workshop on Information Forensics and Security (WIFS 2015), Nov 2015, Rome, Italy. pp. 1-6. ⟨hal-01511889⟩

Share

Metrics

Record views

267

Files downloads

235