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Detection of wood species and defects with NIR
RISE Research Institutes of Sweden, Bioeconomy and Health, Pulp, Paper and Packaging.ORCID iD: 0000-0001-5287-3629
RISE Research Institutes of Sweden, Built Environment, Building and Real Estate.ORCID iD: 0000-0001-6878-3361
2022 (English)Report (Other academic)
Abstract [en]

In this project the possibility to determine different wood species and detect defects on wood cross-sections on logs with hyperspectral near-infrared camera was investigated. This project was a laboratory study where cross-sections of logs were scanned at the wood and fibre analysis laboratory at RISE with near-infrared instrument. Wood samples from different origins and species, with different defects were scanned with a hyperspectral near-infrared camera. Classification models were developed to characterise and classify the different logs. Spruce and pine samples were collected from different sawmills, a group of these samples contained fungal growth. The defects within the collected logs varied and some samples contained decay fungi such as sap- and heart rot as well as non-destructive blue stain. Classifications models to distinguish between different wood species were developed, as well classification models to differentiate between healthy wood and the fungal attack were also developed.

Place, publisher, year, edition, pages
2022. , p. 23
Series
RISE Rapport
National Category
Agriculture, Forestry and Fisheries
Identifiers
URN: urn:nbn:se:ri:diva-73099OAI: oai:DiVA.org:ri-73099DiVA, id: diva2:1856247
Available from: 2024-05-06 Created: 2024-05-06 Last updated: 2025-09-23Bibliographically approved

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Grahn, ThomasYassin, Zakiya

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf