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Knot detection in computed tomography images of partially dried Jack pine (Pinus banksiana Lamb.) and white spruce (Picea glauca (Moench) Voss) logs from a Nelder type plantation
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Wood Science and Engineering.ORCID iD: 0000-0003-4530-0536
University of British Columbia, Vancouver .
Natural Resources Canada, Canadian Wood Fibre Centre, Québec, Canada.
Ministère des Forêts, de la Faune et des Parcs, Québec, Canada.
Number of Authors: 4
2017 (English)In: Canadian Journal of Forest Research, ISSN 0045-5067, E-ISSN 1208-6037Article in journal (Refereed) Epub ahead of print
Abstract [en]

X-ray computed tomography (CT) of logs means possibilities for optimizing breakdown in sawmills. This depends on accurate detection of knots to assess internal quality. However, as logs are stored they dry to some extent, and this drying affects the density variation in the log, and therefore the X-ray images. For this reason it is hypothetically difficult to detect log features in partially dried logs using X-ray CT. This paper investigates the effect of improper heartwood-sapwood border detection, possibly due to partial drying, on knot detection in jack pine (Pinus banksiana Lamb.) and white spruce (Picea glauca (Moench) Voss) logs from New Brunswick, Canada. An automatic knot detection algorithm was compared to manual reference knot measurements, and the results showed that knot detection was affected by detected heartwood shape. It was also shown that logs can be sorted into two groups based on how well the heartwood-sapwood border is detected, to separate logs with a high knot detection rate from those with a low detection rate. In that way, a decision can be made whether or not to trust the knot models obtained from CT scanning. This can potentially aid both sawmills and researchers working with log models based on CT.

Place, publisher, year, edition, pages
2017.
Keyword [en]
CT scanning, jack pine, knot detection, white spruce
National Category
Other Mechanical Engineering
Research subject
Wood Science and Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-41897DOI: 10.1139/cjfr-2016-0423OAI: oai:DiVA.org:ltu-41897DiVA: diva2:1015131
Available from: 2016-10-04 Created: 2016-10-04 Last updated: 2017-04-04

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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  • nn-NB
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  • Other locale
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