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Automated knot detection for high speed computed tomography on Pinus sylvestris L. and Picea abies (L.) Karst. using ellipse fitting in concentric surfaces
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Wood Science and Engineering.
SP Technical Research Institute of Sweden, Skellefteå.
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Wood Science and Engineering.
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Wood Science and Engineering.
2013 (English)In: Computers and Electronics in Agriculture, ISSN 0168-1699, E-ISSN 1872-7107, Vol. 96, p. 238-245Article in journal (Refereed) Published
Abstract [en]

High speed industrial computed tomography (CT) scanning of sawlogs is new to the sawmill industry and therefore there are no properly evaluated algorithms for detecting knots in such images. This article presents an algorithm that detects knots in CT images of logs by segmenting the knots with variable thresholds on cylindrical shells of the CT images. The knots are fitted to ellipses and matched between several cylindrical shells. Parameterized knots are constructed using regression models from the matched knot ellipses. The algorithm was tested on a variety of Scandinavian Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst.) with a knot detection rate of 88–94% and generating about 1% falsely detected knots.

Place, publisher, year, edition, pages
2013. Vol. 96, p. 238-245
National Category
Other Mechanical Engineering
Research subject
Wood Technology
Identifiers
URN: urn:nbn:se:ltu:diva-8418DOI: 10.1016/j.compag.2013.06.003ISI: 000323795700022Scopus ID: 2-s2.0-84880384633Local ID: 6ee1639c-6afa-4b91-8c86-8608b761e1ebOAI: oai:DiVA.org:ltu-8418DiVA, id: diva2:981356
Note
Validerad; 2013; 20130702 (andbra)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved

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Johansson, ErikSkog, JohanFredriksson, Magnus

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  • apa
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  • de-DE
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  • Other locale
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