<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Accurate qualitative evaluation of grown and harvested wood is a key issue from the point of view of its subsequent economic evaluation. With the current trend of global climate change and large volumes of wood damaged by harmful agents, automated methods of wood quality assessment are becoming more and more important. The work aimed to verify the applicability and significance of the results of using the acoustic tomograph for the qualitative assessment of selected tree species logs. Ten samples of log sections of non-coniferous and coniferous trees were evaluated, on which an image analysis of qualitative features was performed on a cross-section from their digital photograph and the image output of an acoustic tomograph software. The results were compared with each other and the accuracy of qualitative feature identification by acoustic tomograph was evaluated. At the same time, the results of the image analysis of the qualitative feature were compared with its assessment through STN EN 1309-3. It was shown that, when evaluated according to the Standard, qualitative features were overestimated by an average of 29.19% compared to the acoustic tomograph and by 28.22% compared to the digital photograph. The use of the acoustic tomograph confirmed a good level of accuracy in the identification of qualitative features even on logs of harvested wood, although it is primarily intended for the qualitative evaluation of standing trees.</p>
</abstract>

Accurate qualitative evaluation of grown and harvested wood is a key issue from the point of view of its subsequent economic evaluation. With the current trend of global climate change and large volumes of wood damaged by harmful agents, automated methods of wood quality assessment are becoming more and more important. The work aimed to verify the applicability and significance of the results of using the acoustic tomograph for the qualitative assessment of selected tree species logs. Ten samples of log sections of non-coniferous and coniferous trees were evaluated, on which an image analysis of qualitative features was performed on a cross-section from their digital photograph and the image output of an acoustic tomograph software. The results were compared with each other and the accuracy of qualitative feature identification by acoustic tomograph was evaluated. At the same time, the results of the image analysis of the qualitative feature were compared with its assessment through STN EN 1309-3. It was shown that, when evaluated according to the Standard, qualitative features were overestimated by an average of 29.19% compared to the acoustic tomograph and by 28.22% compared to the digital photograph. The use of the acoustic tomograph confirmed a good level of accuracy in the identification of qualitative features even on logs of harvested wood, although it is primarily intended for the qualitative evaluation of standing trees.

The use of the acoustic tomograph and digital image analysis in the qualitative assessment of harvested timber – case study

Central European Forestry Journal

This work is licensed under the Creative Commons Attribution 4.0 International License.

Accurate qualitative evaluation of grown and harvested wood is a key issue from the point of view of its subsequent economic evaluation. With the current trend...

The use of the acoustic tomograph and digital image analysis in the qualitative assessment of harvested timber – case study

Online veröffentlicht: 18. Mai 2023

Seitenbereich: 106 - 111

DOI: https://doi.org/10.2478/forj-2022-0021

Schlüsselwörter
wood logs, qualitative sorting, qualitative feature, image analysis, acoustic tomograph, ImageJ software

© 2023 Miloš Gejdoš et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

The use of the acoustic tomograph and digital image analysis in the qualitative assessment of harvested timber – case study

Online veröffentlicht: 18. Mai 2023

Seitenbereich: 106 - 111

DOI: https://doi.org/10.2478/forj-2022-0021

Schlüsselwörterwood logs, qualitative sorting, qualitative feature, image analysis, acoustic tomograph, ImageJ software

© 2023 Miloš Gejdoš et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
wood logs, qualitative sorting, qualitative feature, image analysis, acoustic tomograph, ImageJ software