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Cool, J., Fredriksson, M. & Avramidis, S. (2019). Automatic knot detection in coarse resolution cone-beam CT images of softwood logs. Forest products journal
Open this publication in new window or tab >>Automatic knot detection in coarse resolution cone-beam CT images of softwood logs
2019 (English)In: Forest products journal, ISSN 0015-7473Article in journal (Refereed) Accepted
National Category
Wood Science Other Mechanical Engineering
Research subject
Wood Science and Engineering
Identifiers
urn:nbn:se:ltu:diva-65293 (URN)
Available from: 2017-08-24 Created: 2017-08-24 Last updated: 2019-03-25
Fredriksson, M., Cool, J. & Stavros, A. (2019). Automatic Knot Detection in Coarse-Resolution Cone-Beam Computed Tomography Images of Softwood Logs. Forest products journal, 69(3), 185-187
Open this publication in new window or tab >>Automatic Knot Detection in Coarse-Resolution Cone-Beam Computed Tomography Images of Softwood Logs
2019 (English)In: Forest products journal, ISSN 0015-7473, Vol. 69, no 3, p. 185-187Article in journal (Refereed) Published
Abstract [en]

X-ray computed tomography (CT) scanning of sawmill logs is associated with costly and complex machines. An alternative scanning solution was developed, but its data have not been evaluated regarding detection of internal features. In this exploratory study, a knot detection algorithm was applied to images of four logs to evaluate its performance in terms of knot position and size. The results were a detection rate of 67 percent, accurate position, and inaccurate size. Although the sample size was small, it was concluded that automatic knot detection in coarse resolution CT images of softwoods is feasible, albeit for knots of sufficient size.

Place, publisher, year, edition, pages
Forest Products Society, 2019
National Category
Other Mechanical Engineering
Research subject
Wood Science and Engineering
Identifiers
urn:nbn:se:ltu:diva-76189 (URN)10.13073/FPJ-D-19-00008 (DOI)000484574100002 ()
Note

Validerad;2019;Nivå 2;2019-10-01 (johcin)

Available from: 2019-10-01 Created: 2019-10-01 Last updated: 2019-10-01Bibliographically approved
Olofsson, L., Broman, O., Skog, J., Fredriksson, M. & Sandberg, D. (2019). Multivariate product adapted grading of Scots pine sawn timber for an industrial customer, part 1: Method development. Wood Material Science & Engineering, 14(6), 428-436
Open this publication in new window or tab >>Multivariate product adapted grading of Scots pine sawn timber for an industrial customer, part 1: Method development
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2019 (English)In: Wood Material Science & Engineering, ISSN 1748-0272, E-ISSN 1748-0280, Vol. 14, no 6, p. 428-436Article in journal (Refereed) Published
Abstract [en]

Rule-based automatic grading (RBAG) of sawn timber is a common type of sorting system used in sawmills, which is intricate to customise for specific customers. This study further develops an automatic grading method to grade sawn timber according to a customer’s resulting product quality. A sawmill’s automatic sorting system used cameras to scan the 308 planks included in the study. Each plank was split at a planing mill into three boards, each planed, milled, and manually graded as desirable or not. The plank grade was correlated by multivariate partial least squares regression to aggregated variables, created from the sorting system’s measurements at the sawmill. Grading models were trained and tested independently using 5-fold cross-validation to evaluate the grading accuracy of the holistic-subjective automatic grading (HSAG), and compared with a resubstitution test. Results showed that using the HSAG method at the sawmill graded on average 74% of planks correctly, while 83% of desirable planks were correctly identified. Results implied that a sawmill sorting station could grade planks according to a customer’s product quality grade with similar accuracy to HSAG conforming with manual grading of standardised sorting classes, even when the customer is processing the planks further.

Place, publisher, year, edition, pages
Taylor & Francis, 2019
Keywords
Sawn timber, visual grading, customer adoption, discriminant analysis
National Category
Wood Science Other Mechanical Engineering
Research subject
Wood Science and Engineering
Identifiers
urn:nbn:se:ltu:diva-73967 (URN)10.1080/17480272.2019.1617779 (DOI)
Funder
Vinnova, 2018-02749
Note

Validerad;2019;Nivå 2;2019-10-10 (johcin)

Available from: 2019-05-16 Created: 2019-05-16 Last updated: 2019-10-16Bibliographically approved
Olofsson, L., Broman, O., Skog, J., Fredriksson, M. & Sandberg, D. (2019). Multivariate Product Adapted Grading of Scots Pine Sawn Timber for an Industrial Customer, Part 2: Robustness to Disturbances. Wood Material Science & Engineering, 14(6), 420-427
Open this publication in new window or tab >>Multivariate Product Adapted Grading of Scots Pine Sawn Timber for an Industrial Customer, Part 2: Robustness to Disturbances
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2019 (English)In: Wood Material Science & Engineering, ISSN 1748-0272, E-ISSN 1748-0280, Vol. 14, no 6, p. 420-427Article in journal (Refereed) Published
Abstract [en]

Holistic-subjective automatic grading (HSAG) of sawn timber by an industrial customer's product outcome is possible through the use of multivariate partial least squares discriminant analysis (PLS-DA), shown by part one of this two-part study. This second part of the study aimed at testing the robustness to disturbances of such an HSAG system when grading Scots Pine sawn timber partially covered in dust. The set of 308 clean planks from part one of this study, and a set of 310 dusty planks, that by being stored inside a sawmill accumulated a layer of dust, were used. Cameras scanned each plank in a sawmill's automatic sorting system that detected selected feature variables. The planks were then split and processed at a planing mill, and the product grade was correlated to the measured feature variables by partial least squares regression. Prediction models were tested using 5-fold cross-validation in four tests and compared to the reference result of part one of this study. The tests showed that the product adapted HSAG could grade dusty planks with similar or lower grading accuracy compared to grading clean planks. In tests grading dusty planks, the disturbing effect of the dust was difficult to capture through training.

Place, publisher, year, edition, pages
Taylor & Francis, 2019
Keywords
Sawn timber, visual grading, customer adoption, discriminant analysis
National Category
Wood Science Other Mechanical Engineering
Research subject
Wood Science and Engineering
Identifiers
urn:nbn:se:ltu:diva-73854 (URN)10.1080/17480272.2019.1612944 (DOI)000469741800001 ()2-s2.0-85065546163 (Scopus ID)
Funder
Vinnova, 2018-02749
Note

Validerad;2019;Nivå 2;2019-10-16 (johcin)

Available from: 2019-05-06 Created: 2019-05-06 Last updated: 2019-10-16Bibliographically approved
Fredriksson, M. & Brännström, M. (2018). Technical solutions to increase competitiveness of cross-laminated timber from the Nordic countries: an overview. In: : . Paper presented at 2018 World Conference on Timber Engineering, Seoul, South Korea, 20-23 Aug 2018.
Open this publication in new window or tab >>Technical solutions to increase competitiveness of cross-laminated timber from the Nordic countries: an overview
2018 (English)Conference paper, Published paper (Refereed)
National Category
Wood Science Other Mechanical Engineering
Research subject
Wood Science and Engineering
Identifiers
urn:nbn:se:ltu:diva-66245 (URN)
Conference
2018 World Conference on Timber Engineering, Seoul, South Korea, 20-23 Aug 2018
Available from: 2017-10-24 Created: 2017-10-24 Last updated: 2018-09-12
Cool, J., Fredriksson, M., Stephen, J. D., Mabee, W. E., Avramidis, S. & Bull, G. Q. (2017). An Integrated Forest Products Cluster for Off-Grid Lumber Production Using Biomass CHP in Remote Indigenous Communities. In: : . Paper presented at The 2017 IUFRO All-Division 5 (Forest Products) Conference, Vancouver, BC June 12th–16th.
Open this publication in new window or tab >>An Integrated Forest Products Cluster for Off-Grid Lumber Production Using Biomass CHP in Remote Indigenous Communities
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2017 (English)Conference paper, Oral presentation with published abstract (Refereed)
National Category
Wood Science
Research subject
Wood Science and Engineering
Identifiers
urn:nbn:se:ltu:diva-60473 (URN)
Conference
The 2017 IUFRO All-Division 5 (Forest Products) Conference, Vancouver, BC June 12th–16th
Available from: 2016-11-16 Created: 2016-11-16 Last updated: 2017-11-24Bibliographically approved
Olofsson, L., Broman, O., Fredriksson, M., Skog, J. & Sandberg, D. (2017). Customer adapted grading of Scots pine sawn timber: a multivariate method approach. In: Zbiec M & Orlowski K (Ed.), 23rd International wood machining seminar: proceedings : 28. - 31. 5. 2017, Warsaw, Poland. Paper presented at 23rd International Wood Machining Seminar (IWMS-23), War saw, Poland, May 28-31 2017 (pp. 360-361). Warsaw: Warsaw university of life sciences
Open this publication in new window or tab >>Customer adapted grading of Scots pine sawn timber: a multivariate method approach
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2017 (English)In: 23rd International wood machining seminar: proceedings : 28. - 31. 5. 2017, Warsaw, Poland / [ed] Zbiec M & Orlowski K, Warsaw: Warsaw university of life sciences , 2017, p. 360-361Conference paper, Published paper (Refereed)
Abstract [en]

At Scandinavian softwood sawmills, the most common system for grading of sawn timber in dry conditions is optical scanning equipment together with a rule-based automatic grading system (RBAG). The procedure to define new grading rules towards a customer with specified requirements is a time-consuming work for sawmills and is rarely implemented in a satisfactory way neither for the customer nor for the sawmill. An important consequence is that sawmills will, in general, not be able to deliver products that utilize the full potential of the quality distribution of the sawn timber produced at the sawmill. Their customers will get products with mismatch in desired and delivered quality grades. Thus, there is a need for a methodology that facilitates time and cost effective grading toward specific customers’ needs. The objective of the study was to further develop and validate a method that complements the RBAG by a holistic-subjective automatic grading (HSAG) approach - using multivariate regression models.In the study, 790 Scots pine boards with cross-section dimensions of 38×150 mm and length between 3.4 m and 5.6 m were manually graded according to the preferences of a large-volume customer, and also scanned and graded by an RBAG system calibrated for the same customer. Multivariate models for prediction of board grade, based on aggregated knot variables obtained from the scanning, were calibrated using partial least squares regression. The results show that prediction of board grades by the multivariate models were more correct than the grading by the RBAG system. The prediction of board grades based on multivariate models resulted in 84% of the boards graded correctly, according to the manual grading, while the corresponding number was 64% for the RBAG system. In a follow up grading test the accuracy of the two systems were 95% and 81%, respectively.

Place, publisher, year, edition, pages
Warsaw: Warsaw university of life sciences, 2017
National Category
Agricultural and Veterinary sciences Wood Science Other Mechanical Engineering
Research subject
Wood Science and Engineering
Identifiers
urn:nbn:se:ltu:diva-65840 (URN)978-83-948046-0-2 (ISBN)
Conference
23rd International Wood Machining Seminar (IWMS-23), War saw, Poland, May 28-31 2017
Available from: 2017-09-26 Created: 2017-09-26 Last updated: 2017-11-24Bibliographically approved
Cool, J., Fredriksson, M. & Avramidis, S. (2017). Knot detection in coarse resolution CT images of logs. In: International Wood Machining Seminar (IWMS-23): . Paper presented at 23rd International Wood Machining Seminar, Warsaw, Poland, 28-31 May 2017.
Open this publication in new window or tab >>Knot detection in coarse resolution CT images of logs
2017 (English)In: International Wood Machining Seminar (IWMS-23), 2017Conference paper, Published paper (Refereed)
Abstract [en]

The use of X-ray computed tomography (CT) scanning of logs in sawmill is becoming a reality in the last few years, usually with rather costly and complex machines resembling medical scanners. However, a scanning solution has been developed that is less costly and more robust, and therefore more suited for sawmill needs. The rather coarse data from this machine has not been fully evaluated regarding possibilities to detect internal features such as knots. In this study, a knot detection algorithm developed for medical scanners was applied to images from a coarse resolution scanner, from four different logs of various species, and with different image resolution. The objective was to see if it was possible to detect knots automatically in the images. If so, the aim was to calculate the knot detection rate and the accuracy of detected knot size and position. These numbers were calculated compared to manually measured reference knots. This resulted in a knot detection rate of about 53 % overall, and a well detected knot position, but poorly detected knot size. It is possible to observe a certain difference between species and reconstruction resolution, however the material is too small to draw any definite conclusions. As a preliminary study, it provides input for further investigation on knot detection in coarse resolution X-ray CT images. Future work involves scanning more logs to get more data, and to pinpoint the resolution needed for accurate knot detection using the current algorithm.

National Category
Wood Science Other Mechanical Engineering
Research subject
Wood Science and Engineering
Identifiers
urn:nbn:se:ltu:diva-59964 (URN)
Conference
23rd International Wood Machining Seminar, Warsaw, Poland, 28-31 May 2017
Available from: 2016-10-26 Created: 2016-10-26 Last updated: 2017-11-24Bibliographically approved
Fredriksson, M., Cool, J. & Avramidis, S. (2017). Knot detection in computed tomography images of partially dried Jack pine (Pinus banksiana Lamb.) and white spruce (Picea glauca (Moench) Voss) logs. In: International Wood Machining Seminar (IWMS-23): . Paper presented at 23rd International Wood Machining Seminar, Warsaw, Poland, 28-31 May 2017.
Open this publication in new window or tab >>Knot detection in computed tomography images of partially dried Jack pine (Pinus banksiana Lamb.) and white spruce (Picea glauca (Moench) Voss) logs
2017 (English)In: International Wood Machining Seminar (IWMS-23), 2017Conference paper, Published paper (Refereed)
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 in the log yard they dry to a certain 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. The objective of this research was to investigate the effect of 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 measurements for this purpose, and the results show that knot detection was clearly affected by partial drying. Because dried heartwood and sapwood have similar densities, the algorithm had difficulties detecting the heartwood-sapwood border. Based on how well the heartwood-sapwood border was detected, it was statistically possible to sort logs into two groups: 1) Low knot detection rate, and 2) High knot detection rate. In that way, a decision can be made whether or not to trust the knot models obtained from CT scanning. Therefore, logs that are partially dried out and fall in the low knot detection rate should be handled cautiously because the optimization results based on CT knot detection cannot be fully trusted. Sawing of these logs could be optimized using only their outer shape, ignoring internal quality. Similarly, only logs having a regular heartwood shape should be used when scanning logs for research purposes or in databases of CT scanned logs. Finally, a larger knot detection rate was obtained for Jack pine. This could have been facilitated by the fact that pine trees usually have larger but less numerous knots than spruce trees.

National Category
Wood Science Other Mechanical Engineering
Research subject
Wood Science and Engineering
Identifiers
urn:nbn:se:ltu:diva-59965 (URN)
Conference
23rd International Wood Machining Seminar, Warsaw, Poland, 28-31 May 2017
Available from: 2016-10-26 Created: 2016-10-26 Last updated: 2017-11-24Bibliographically approved
Fredriksson, M., Cool, J., Duchesne, I. & Belley, D. (2017). 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. Canadian Journal of Forest Research, 47(7), 910-915
Open this publication in new window or tab >>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
2017 (English)In: Canadian Journal of Forest Research, ISSN 0045-5067, E-ISSN 1208-6037, Vol. 47, no 7, p. 910-915Article in journal (Refereed) Published
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.

Abstract [fr]

La tomographie aux rayons X assistée par ordinateur (TO) des billes offre la possibilité d'optimiser le débitage dans les scieries. Cela repose sur la précision avec laquelle les nœuds sont détectés pour évaluer la qualité interne. Cependant, lorsque les billes sont entreposées, elles sèchent jusqu'à un certain point et cela influence la variation de la densité dans les billes, et par conséquent les images radiologiques. Pour cette raison, il est hypothétiquement difficile de détecter les caractéristiques dans les billes partiellement séchées à l'aide de la TO. Cet article étudie l'effet de l'erreur de détection de la limite entre le bois de cœur et le bois d'aubier, potentiellement attribuable au séchage partiel, sur la détection des nœuds dans des billes de pin gris ( Pinus banksiana Lamb.) et d'épinette blanche ( Picea glauca (Moench) Voss) provenant du Nouveau-Brunswick, au Canada. Un algorithme de détection automatisée des nœuds a été comparé à des mesures de référence de nœuds effectuées manuellement. Les résultats ont montré que la forme du bois de cœur qui est détectée influence la détection des nœuds. Il a également été démontré que les billes peuvent être réparties en deux groupes sur la base de la justesse de la détection de la limite entre le bois de cœur et le bois d'aubier, ce qui permet de séparer les billes chez lesquelles le taux de détection des nœuds est élevé de celles chez lesquelles le taux de détection des nœuds est faible. De cette façon, on peut prendre la décision de faire confiance ou non aux nœuds modélisés obtenus avec le balayage par TO. Cela peut possiblement aider tant les scieries que chercheurs qui utilisent la modélisation des billes fondée sur la TO

Place, publisher, year, edition, pages
Canadian Science Publishing, 2017
Keywords
CT scanning, jack pine, knot detection, white spruce
National Category
Other Mechanical Engineering
Research subject
Wood Science and Engineering
Identifiers
urn:nbn:se:ltu:diva-41897 (URN)10.1139/cjfr-2016-0423 (DOI)000404460700007 ()2-s2.0-85021625608 (Scopus ID)
Note

Validerad;2017;Nivå 2;2017-07-03 (andbra)

Available from: 2016-10-04 Created: 2016-10-04 Last updated: 2018-07-10Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0003-4530-0536

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