Evaluation of Knots and Fibre Orientation by Gradient Analysis in X-ray Computed Tomography Images of Wood

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Fältnamn	Indikatorer	Metadata
000		05664naa a2200397 4500
001		oai:DiVA.org:ltu-101289
003		SwePub
008		230911s2023 \| \|\|\|\|\|\|\|\|\|\|\|000 \|\|eng\|
024	7	a https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-1012892 URI
040		a (SwePub)ltu
041		a engb eng
042		9 SwePub
072	7	a vet2 swepub-contenttype
072	7	a kon2 swepub-publicationtype
100	1	a Huber, Johannes Albert Josef,c PhD,d 1989-u Luleå tekniska universitet,Träteknik4 aut0 (Swepub:ltu)johhub
245	1 0	a Evaluation of Knots and Fibre Orientation by Gradient Analysis in X-ray Computed Tomography Images of Wood
264	1	a Barcelona :b International Center for Numerical Methods in Engineering (CIMNE),c 2023
338		a electronic2 rdacarrier
520		a The mechanical properties of wood are governed by growth-dependent structures on themicro- and macroscopic level, which are subject to natural variation. Numerical modelsof wood on a scale of individual pieces of sawn timber may need to account e.g. for thegrowth ring orientation or the presence of knots and their effects on the local materialorientation, i.e. the variation of the fibre coordinate system (FCS). The FCS is composedof the mutually orthogonal longitudinal (l), radial (r) and tangential (t) directions. Agrowth surface represents a region of equal age, i.e. a former growth front of the tree,and at each point on a growth surface, the r direction consequently represents the surfacenormal. Growth surfaces surrounding a knot are usually approximated by analyticalsurfaces, onto which the l direction is modelled by hydrodynamic flow fields in lateral andby polynomials in the vertical direction, like in [1].A data-driven method used for detecting the location of knots and eliciting the in-planeprojection of the l direction on the surface of sawn timber is optical scanning combinedwith laser tracheid scanning [2]. A disadvantage of this method is that the internalstructure of the scanned timber remains unknown and needs to be extrapolated, againbased on assumptions of growth in wood. X-ray computed tomography (CT) of woodprovides images of the internal density distribution from which features like the pith, thegrowth rings, knots and defects can be extracted by image analysis.In a recent study [3], the local FCSs around knots were reconstructed by density gradientanalysis in CT images, on which finite element models were based for predicting thebending behaviour of sawn timber. Growth surfaces in wood represent regions of nearlyconstant density and can therefore be analysed in CT images by gradient-based methods.The goal of the present study was therefore to study how the gradient of the density fieldderived from CT images of wood can be used to determine growth surfaces, the region ofknots, the border between dead and live knot, and the locally varying FCSs.The material studied was comprised of small log sections of Scots pine (pinus sylvestris)(approximate diameters of 50 mm - 300 mm and length 250 mm) containing knot whorls,which were dried to fibre saturation. CT scans were acquired at a voxel size of 0.5 × 0.5 ×0.5 mm3 yielding a 3D image J(x, y, z). After scanning, the sections were cut throughthe centrelines of the knots and manual measurements were conducted of the dead knotborder, i.e. the position along the boundary of a knot after which a knot died off. At this border, the diameter of the knot stops increasing and the surrounding fibres grow aroundthe knot rather than merging with it. As the tree continues to grow, this will eventuallylead to bark being encased around the knot inside the tree.A purely data-driven analysis was performed based on the partial derivatives Jx , Jy , Jz ,from which the gradient structure tensor (GST) was constructed, see equation 1, where wσ is a Gaussian convolutional kernel. The eigenvalues and eigenvectors of the GSTwere extracted for each voxel and the resulting vector field was used in the subsequentanalyses. Equivalently, second order derivatives were studied to study curvature.The results indicate that gradient-based analyses on CT images of wood can be usedto approximate the locally varying FCSs around knots, see Figure 1 and that they mayfacilitate the determination of the region of dead and live knots.
650	7	a LANTBRUKSVETENSKAPERx Lantbruksvetenskap, skogsbruk och fiskex Trävetenskap0 (SwePub)401052 hsv//swe
650	7	a AGRICULTURAL SCIENCESx Agriculture, Forestry and Fisheriesx Wood Science0 (SwePub)401052 hsv//eng
650	7	a NATURVETENSKAPx Data- och informationsvetenskapx Datorseende och robotik0 (SwePub)102072 hsv//swe
650	7	a NATURAL SCIENCESx Computer and Information Sciencesx Computer Vision and Robotics0 (SwePub)102072 hsv//eng
653		a gradient structure tensor
653		a hessian
653		a partial derivatives
653		a growth surfaces
653		a dead knot
653		a Träteknik
653		a Wood Science and Engineering
700	1	a Olofsson, Linusu Luleå tekniska universitet,Träteknik4 aut0 (Swepub:ltu)linolo
710	2	a Luleå tekniska universitetb Träteknik4 org
773	0	t CompWood2023: Computational Methods in Wood Mechanicsd Barcelona : International Center for Numerical Methods in Engineering (CIMNE)g , s. 143-144q <143-144z 9788412322279
856	4	u https://congressarchive.cimne.com/compwood_2023/assets/book_of_abstracts_compwood_2023.pdfy Book of abstracts
856	4	u https://ltu.diva-portal.org/smash/get/diva2:1795721/FULLTEXT01.pdfx primaryx Raw objecty fulltext:print
856	4 8	u https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-101289

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