Automatic knot detection and measurements from X-ray CT images of wood: A review and validation of an improved algorithm on softwood samples

Longuetaud, Fleur; Mothe, Frédéric; Kerautret, Bertrand; Krähenbühl, Adrien; Hory, L.; Leban, Jean-Michel; Debled-Rennesson, Isabelle

doi:10.1016/j.compag.2012.03.013

Cited by 83 publications

(45 citation statements)

References 51 publications

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“…Since CT scanning uses X-rays, internal log features with density variation can be distinguished. Examples of such features are heartwood-sapwood (Longuetaud et al 2007), 23 knots (Bhandarkar et al 1999, Longuetaud et al 2012 Johansson et al 2013), checks (Bhandarkar et al 1999, Andreu andRinnhofer 2003, 25 Wehrhausen et al 2012), decay (Schmoldt et al 1996) and resin pockets (Oja and Temnerud 26 1999). Recent studies on automatic knot detection in CT images of logs include Krähenbühl et 27 al.…”

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confidence: 99%

Knot detection in computed tomography images of partially dried jack pine (Pinus banksiana) and white spruce (Picea glauca) logs from a Nelder type plantation

et al. 2017

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1X-ray computed tomography (CT) of logs means possibilities for optimizing breakdown in 2 sawmills. This depends on accurate detection of knots to assess internal quality. However, as 3 logs are stored they dry to some extent, and this drying affects the density variation in the log, 4 and therefore the X-ray images. For this reason it is hypothetically difficult to detect log 5 features in partially dried logs using X-ray CT. This paper investigates the effect of improper 6 heartwood-sapwood border detection, possibly due to partial drying, on knot detection in jack 7 pine (Pinus banksiana Lamb.) and white spruce (Picea glauca (Moench) Voss) logs from New 8 Brunswick, Canada. An automatic knot detection algorithm was compared to manual 9 reference knot measurements, and the results showed that knot detection was affected by 10 detected heartwood shape. It was also shown that logs can be sorted into two groups based on 11 how well the heartwood-sapwood border is detected, to separate logs with a high knot 12 detection rate from those with a low detection rate. In that way, a decision can be made 13 whether or not to trust the knot models obtained from CT scanning. This can potentially aid 14 both sawmills and researchers working with log models based on CT.

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confidence: 99%

Knot detection in computed tomography images of partially dried jack pine (Pinus banksiana) and white spruce (Picea glauca) logs from a Nelder type plantation

et al. 2017

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“…Efficient software makes virtual sawing or veneer cutting of a log described by 3D tomography a reality (Longuetaud et al 2007(Longuetaud et al , 2012Mothe et al 2002;Roussel et al 2014), opening the door to better sawing patterns in a sawmill for a known resource and a given market (Berglund et al 2014). By using a simple geometrical transformation to simulate the veneering process, the tree stem description given by growth and yield simulation software (Dufour-Kowalski et al 2012) allows the delivery of virtual maps of wood properties in veneers (grain angle and wood density) and prediction of the properties of secondary transformation products (Constant et al 2003;Mothe et al 2002).…”

Section: Wood Density Branching and Primary Conversionmentioning

confidence: 99%

Wood machining with a focus on French research in the last 50 years

Thibaut

Denaud

Collet

et al. 2016

Annals of Forest Science

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Abstract& Key message Wood machining is compulsory both for timber separation and the surfacing of wooden objects. The anisotropy, cellular nature and multi-scale level organisation of wood make its cutting complicated to study. During the last 50 years, most of the wood machining subjects were covered by French teams. & Context Woodcutting is a very old technology but scientific research is scarce on the subject. In the last 50 years, much work on basic mechanisms as well as on industrial processes has been done in France. In primary conversion such as sawing, veneer cutting or green wood chipping, huge progress comes from automation and the possibility of linking the process to log and product quality through new sensors. In secondary processing, much has been done on the links between the cutting process, surface qualification and the properties of these surfaces for further processing, such as gluing or coating. Tool wear depends on the cutting process, timber quality and species. Tradeoffs are required in tool technology and coating technologies may improve tool life. & Conclusion A large amount of knowledge and innovation has come from 50 years of worldwide research effort, with France being particularly active in this period. The transfer of skills from metals cutting industry was often a key, but much is needed to move closer to both metal cutting sector and woodcutting skills among craftsmen.

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“…X-ray tomography is a nondestructive 3D imaging technique that allows the study of interior structures of an object ( Landis and Keane 2010 ). Industrial X-ray tomography scanners are successful for determination of wood properties in terms of internal log features such as pith, growth rings, heartwood and sapwood, knots, and decay ( Wei et al 2011 ;Longuetaud et al 2012 ).…”

Section: Introductionmentioning

confidence: 99%

Cork structural discontinuities studied with X-ray microtomography

et al. 2015

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: Cork is a natural cellular material with a rather unique set of properties, and its best known application is as stopper for wine bottles. The cork tissue contains structural discontinuities, for example, lenticular channels (LCh), that influence the in-use performance of cork products. X-ray microtomography, in combination with image analysis, has been used for cork characterisation and provided new insights into the three-dimensional location of discontinuities, which are hidden for a visual inspection. It was demonstrated that the presence of LCh is positively correlated with cork density, and the void fraction of LCh in the lower part of a cork stopper is strongly related to the oxygen ingress in the bottle during the first month after bottling. The results contribute to better understanding the natural variation of cork properties.

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Automatic knot detection and measurements from X-ray CT images of wood: A review and validation of an improved algorithm on softwood samples

Cited by 83 publications

References 51 publications

Knot detection in computed tomography images of partially dried jack pine (Pinus banksiana) and white spruce (Picea glauca) logs from a Nelder type plantation

Knot detection in computed tomography images of partially dried jack pine (Pinus banksiana) and white spruce (Picea glauca) logs from a Nelder type plantation

Wood machining with a focus on French research in the last 50 years

Cork structural discontinuities studied with X-ray microtomography

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