nach oben

Wood Science and Technology

Erschienen in:

18.05.2022 | Original

Individual wood board tracing method using oriented fast and rotated brief method in the wood traceability system

verfasst von: Yongke Sun, Guanben Du, Qizhao Lin, Lihui Zhong, Youjie Zhao, Jian Qiu, Yong Cao

Erschienen in: Wood Science and Technology | Ausgabe 3/2022

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Due to the economic, social, and legal requirements, individual wood identity recognition is a crucial technology required in traceability systems, such as the wood block chain system. Traditionally, labeling is a widely used technology which sticks a code label on the wood entity. It can be used to find out the information related to the entity from the traceability system by scanning the code labels. However, many kinds of labels are easily switched and falsified in illegal activities. This study proposed a new security label method that extracts the innate feature as wood fingerprint to prevent the label falsify problem. This method acquired the cross-section image of log or wood board and extracted the oriented fast and rotated brief (ORB) features to identify the individual entities. It is safe because the feature of the wood texture is innate and cannot be transferred from one to another. Furthermore, this features is unique because of the anisotropy of wood. An image acquisition method was presented. A position was marked as the fingerprint area at the cross section of the wood board, and the image of the fingerprint area was acquired by using a camera with a 20× magnifying glass. The individual wood board tracking method based on the ORB was employed to identify the wood entity. The key point set was described by a invariant rotation descriptor, and it can be used as a fingerprint to recognize the wood board by comparing the marked area images in the wood traceability system. In the experiments, 80 woodblocks were chosen as the tracer objects, and 10 places were marked at each cross section of the board. The results showed that this method has high recognition accuracy and robustness. The recognition accuracy reached 100%, and this method still retained high accuracy even when different cameras were used in different environments to acquire the images. This method can be used in the timber trade to trace wood boards or logs and to prevent illegal trading.

Vorheriger Artikel Reliability of tomographic image to represent variation in stem wood properties assessed using confusion matrix metrics

Nächster Artikel Natural dye extracted from Dalbergia cochinchinensis residue with water fastness, mildew resistance and permeability properties for wood staining

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Appelhanz S, Osburg VS, Toporowski W, Schumann M (2016) Traceability system for capturing, processing and providing consumer-relevant information about wood products: system solution and its economic feasibility. J Clean Prod 110:132–148. https://doi.org/10.1016/j.jclepro.2015.02.034CrossRef

Bay H, Ess A, Tuytelaars T, Van Gool L (2008) Speeded-up robust features (SURF). Comput Vis Image Underst 110(3):346–359. https://doi.org/10.1016/j.cviu.2007.09.014CrossRef

Björk A, Erlandsson M, Häkli J, Jaakkola K, Nilsson Å, Nummila K, Puntanen V, Sirkka A (2011) Monitoring environmental performance of the forestry supply chain using RFID. Comput Ind 62(8–9):830–841. https://doi.org/10.1016/j.compind.2011.08.001CrossRef

Chater A, Lasfar A (2020) New approach to the identification of the easy expression recognition system by robust techniques (SIFT, PCA-SIFT, ASIFT and SURF). Telkomnika 18(2):695–704. https://doi.org/10.12928/TELKOMNIKA.v18i2.13726CrossRef

Chen M, Huang J, Lin Z, Guan P, Lin S, Liu X, Liu L (2018) Research on the reform of streamlining administration, delegating more powers, improving regulation and optimizing services for wood products supervision mode. J Insp Quar 28(6):47–51

Dykstra DP, Kuru G, Taylor R, Nussbaum R, Magrath W, Story J (2010) Technologies for wood tracking: Verifying and monitoring the chain of custody and legal compliance in the timber industry. Tech. rep., World bank

Figorilli S, Antonucci F, Costa C, Pallottino F, Raso L, Castiglione M, Pinci E, Del Vecchio D, Colle G, Proto AR, Sperandio G, Menesatti P (2018) A blockchain implementation prototype for the electronic open source traceability of wood along the whole supply chain. Sensors (Switzerland) 18(9):1–12. https://doi.org/10.3390/s18093133CrossRef

Filho PLP, Oliveira LS, Nisgoski S, Britto AS (2014) Forest species recognition using macroscopic images. Mach Vis Appl 25(4):1019–1031. https://doi.org/10.1007/s00138-014-0592-7CrossRef

Godbout J, Bomal C, Farr K, Williamson M, Isabel N (2018) Genomic tools for traceability: opportunities, challenges and perspectives for the canadian forestry sector. For Chron 94(01):75–87. https://doi.org/10.5558/tfc2018-010CrossRef

Harris C, Stephens M (1988) A Combined Corner and Edge Detector. In: Procedings of the Alvey Vision Conference 1988, Alvey Vision Club, pp 147–152, https://doi.org/10.5244/C.2.23

Johansson E, Pahlberg T, Hagman O (2015) Fast visual recognition of scots pine boards using template matching. Comput Electron Agric 118:85–91. https://doi.org/10.1016/j.compag.2015.08.026CrossRef

Kannangara S, Karunarathne S, Ranaweera L, Ananda K, Sooriyapathirana S (2020) Assessment of the applicability of wood anatomy and DNA barcoding to detect the timber adulterations in Sri Lanka. Entific Rep 10(1):4352. https://doi.org/10.1038/s41598-020-61415-2CrossRef

Knowles C, Boston K, Berecibar E (2017) A new method for tagging and tracking logs. Int For Rev 19(3):294–305. https://doi.org/10.1505/146554817821865036CrossRef

Lindeberg T (2012) Scale invariant feature transform. Scholarpedia 7(5):10491. https://doi.org/10.4249/scholarpedia.10491CrossRef

Lipton ZC, Elkan C, Naryanaswamy B (2014) Optimal Thresholding of Classifiers to Maximize F1 Measure. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Verlag. The Journal’s web site is located at http://springerlink.com/content/105633/, pp 225–239, https://doi.org/10.1007/978-3-662-44851-9_15

Lowe DG (2004) Distinctive Image Feature from Scale-Invariant Key points. Int J Comput Vision 60(2):91–110CrossRef

Lowe AJ, Cross HB (2011) The application of DNA methods to timber tracking and origin verification. IAWA J 32(2):251–262. https://doi.org/10.1163/22941932-90000055CrossRef

Luo C, Yang W, Huang P, Zhou J (2019) Overview of image matching based on ORB algorithm. J Phys Conf Ser 1237:032020. https://doi.org/10.1088/1742-6596/1237/3/032020CrossRef

Ma C, Hu X, Xiao J, Du H, Zhang G (2020) Improved ORB algorithm using three-patch method and local gray difference. Sensors 20(4):975. https://doi.org/10.3390/s20040975CrossRefPubMedCentral

Pahlberg T, Hagman O, Thurley M (2015) Recognition of boards using wood fingerprints based on a fusion of feature detection methods. Comput Electron Agric 111:164–173. https://doi.org/10.1016/j.compag.2014.12.014CrossRef

Qin Y, Xu H, Chen H (2014) Image feature points matching via improved ORB. In: 2014 IEEE International Conference on Progress in Informatics and Computing, IEEE, pp 204–208, https://doi.org/10.1109/PIC.2014.6972325

Rublee E, Rabaud V, Konolige K, Bradski G (2011) ORB: An efficient alternative to SIFT or SURF. In: 2011 International Conference on Computer Vision, IEEE, pp 2564–2571, https://doi.org/10.1109/ICCV.2011.6126544

Schmid JF, Simon SF, Mester R (2020) Features for ground texture based localization—a survey. arXiv:2002.11948

Schraml R, Hofbauer H, Petutschnigg A, Uhl A (2015) Tree log identification based on digital cross-section images of log ends using fingerprint and iris recognition methods. J Math Imag Vis. https://doi.org/10.1007/978-3-319-23192-1_63CrossRef

Schraml R, Charwat-Pessler J, Petutschnigg A, Uhl A (2015a) Towards the applicability of biometric wood log traceability using digital log end images. Comput Electron Agric 119:112–122. https://doi.org/10.1016/j.compag.2015.10.003CrossRef

Schraml R, Entacher K, Petutschnigg A, Young T, Uhl A (2020) Matching score models for hyperspectral range analysis to improve wood log traceability by fingerprint methods. Mathematics 8(7):1071. https://doi.org/10.3390/math8071071CrossRef

Schraml R, Petutschnigg A, Uhl A (2015c) Validation and reliability of the discriminative power of geometric wood log end features. In: IEEE International Conference on Image Processing, pp 3665–3669

Schweingruber FH (2007) Wood Structure and Environment. Springer Series in Wood Science, Springer Berlin Heidelberg, Berlin, Heidelberg, https://doi.org/10.1007/978-3-540-48548-3

Shin D, Hwang Y (2020) The effects of security and traceability of blockchain on digital affordance. Online Inf Rev 44(4):913–932. https://doi.org/10.1108/OIR-01-2019-0013CrossRef

Sun Q, Xu Y, Xiao Y (2019) Research on intelligent wood storage management and monitoring systems based on forestry Internet of Things. Modern Electron Tech 42(20):169–172. https://doi.org/10.16652/j.issn.1004-373x.2019.20.040CrossRef

Tnah LH, Lee SL, Ng KKS, Bhassu S, Othman RY (2012) DNA extraction from dry wood of Neobalanocarpus heimii (Dipterocarpaceae) for forensic DNA profiling and timber tracking. Wood Sci Technol 46(5):813–825. https://doi.org/10.1007/s00226-011-0447-6CrossRef

Tzoulis IK, Andreopoulou ZS, Voulgaridis E (2014) Wood tracking information systems to confront illegal logging. J Agric Inform 5(1):9–17. https://doi.org/10.17700/jai.2014.5.1.130CrossRef

Vieira LC, Gomes NJ, Batchelor JC, Nkansah A, Assimakopoulos P, Ziai MA (2020) RFID over low cost VCSEL-based MMF links: experimental demonstration and distortion study. IET Optoelectron 14(4):149–154CrossRef

Wang J (2013) Pearson correlation coefficient. In: Dubitzky W, Wolkenhauer O, Cho KH, Yokota H (eds) Encyclopedia of systems biology. Springer New York, New York, NY, p 1671. https://doi.org/10.1007/978-1-4419-9863-7_372CrossRef

Wu M (2018) Research on optimization of image fast feature point matching algorithm. EURASIP J Image Video Process 2018(1):106. https://doi.org/10.1186/s13640-018-0354-yCrossRef

Zhang S, Li X, Zong M, Zhu X, Wang R (2018) Efficient kNN classification with different numbers of nearest neighbors. IEEE Trans Neural Netw Learn Syst 29(5):1774–1785. https://doi.org/10.1109/TNNLS.2017.2673241CrossRefPubMed

Zj G (2020) Process of global governance on tackling illegal logging. Ecol Econ 16(01):26–34

Titel: Individual wood board tracing method using oriented fast and rotated brief method in the wood traceability system
verfasst von: Yongke Sun
Guanben Du
Qizhao Lin
Lihui Zhong
Youjie Zhao
Jian Qiu
Yong Cao
Publikationsdatum: 18.05.2022
Verlag: Springer Berlin Heidelberg
Erschienen in: Wood Science and Technology / Ausgabe 3/2022
Print ISSN: 0043-7719
Elektronische ISSN: 1432-5225
DOI: https://doi.org/10.1007/s00226-022-01379-w

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Technik"

Springer Professional "Wirtschaft+Technik"

Weitere Artikel der Ausgabe 3/2022

Reliability of tomographic image to represent variation in stem wood properties assessed using confusion matrix metrics

Relationship between freeze-drying and supercritical drying of cellulosic fibers with different moisture contents based on pore and crystallinity measurements

Interaction of lignin and hemicelluloses in hydrolysate and with stainless steel surface

Modification mechanism of plantation wood via grafting epoxy monomers onto cell walls

Optimizing conditions for using deep eutectic solvents to extract lignin from black liquor

Aminosilane-modified wood sponge for efficient CO2 capture