SmartWoodID—an image collection of large end-grain surfaces to support wood identification systems.
Name
baad034.pdf
Description
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Size
4.37 MB
Format
Adobe PDF
Checksum (CRC64NVME)
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Resource type
Journal article
Date published
January 1, 2023
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
Funder
| Funder name | Awards |
Belgian Federal Science Policy Office, Begium | BRAIN-be 2.0 (Belgian Research Action through Interdisciplinary Networks PHASE 2–2018-2023) - B2/202/P2/SmartWoodID |
Bijzonder Onderzoeksfonds UGent, Belgium | BOF Starting Grant JVdB (BOFSTG2018000701) |
Journal title
Database
Volume
2023
Article number
baad034
Publisher
Oxford University Press (OUP)
Place of publication
Oxford, UK
eISSN
1758-0463
Date accepted
April 19, 2023
Official URL
Rights statement
In Copyright
Additional information
IF = 4.462 (2022-2023)