SmartWoodID-an image collection of large end-grain surfaces to support wood identification systems.

Journal: Database : the journal of biological databases and curation
Published Date:

Abstract

Wood identification is a key step in the enforcement of laws and regulations aimed at combatting illegal timber trade. Robust wood identification tools, capable of distinguishing a large number of timbers, depend on a solid database of reference material. Reference material for wood identification is typically curated in botanical collections dedicated to wood consisting of samples of secondary xylem of lignified plants. Specimens from the Tervuren Wood Collection, one of the large institutional wood collections around the world, are used as a source of tree species data with potential application as timber. Here, we present SmartWoodID, a database of high-resolution optical scans of the end-grain surfaces enriched with expert wood anatomical descriptions of macroscopic features. These can serve as annotated training data to develop interactive identification keys and artificial intelligence for computer vision-based wood identification. The first edition of the database consists of images of 1190 taxa, with a focus on potential timber species from the Democratic Republic of the Congo with at least four different specimens per species included. Database URL https://hdl.handle.net/20.500.12624/SmartWoodID_first_edition.

Authors

  • Ruben De Blaere
    Service of Wood Biology, Royal Museum for Central Africa, Leuvensesteenweg 13, Tervuren 3080, Belgium.
  • Kévin Lievens
    Service of Wood Biology, Royal Museum for Central Africa, Leuvensesteenweg 13, Tervuren 3080, Belgium.
  • Dieter Van Hassel
    Service of Wood Biology, Royal Museum for Central Africa, Leuvensesteenweg 13, Tervuren 3080, Belgium.
  • Victor Deklerck
    Jodrell laboratory, Royal Botanic Gardens, Kew, Richmond, London TW9 3A, UK.
  • Tom De Mil
    TERRA Teaching and Research Center, Gembloux Agro-Bio Tech (Université de Liège), Passage des Déportés 2, Gembloux 5030, Belgium.
  • Wannes Hubau
    Service of Wood Biology, Royal Museum for Central Africa, Leuvensesteenweg 13, Tervuren 3080, Belgium.
  • Joris Van Acker
    UGent-Woodlab, Laboratory of Wood Technology, Department of Environment, Ghent University, Coupure Links 653, Gent 9000, Belgium.
  • Nils Bourland
    Service of Wood Biology, Royal Museum for Central Africa, Leuvensesteenweg 13, Tervuren 3080, Belgium.
  • Jan Verwaeren
    UGent-KERMIT, Research Unit Knowledge-based, Predictive and Spatio-temporal Modelling, Department of Data Analysis and Mathematical Modelling, Ghent University, Coupure Links 653, Gent 9000, Belgium.
  • Jan Van den Bulcke
    UGent-Woodlab, Laboratory of Wood Technology, Department of Environment, Ghent University, Coupure Links 653, Gent 9000, Belgium.
  • Hans Beeckman
    Service of Wood Biology, Royal Museum for Central Africa, Leuvensesteenweg 13, Tervuren 3080, Belgium.