Wood identification is of paramount importance in various fields, including forensic verification of timber origin and detecting illegally logged tropical timber at ports . While DNA analysis has been widely used for this purpose, the cellular-level structure of wood also offers valuable information for species discrimination. This research explores the potential of micro-computed tomography (µCT) systems, with resolutions down to 1µm, to reveal distinct features in wood samples for automatic identification and quantification [2, 4, 5].
In this Master’s thesis, we focus on investigating wood identification through micro-CT using ten exemplary samples of maple and pine wood. All wood samples underwent µCT scanning, and the primary objective is to semantically segment the wood volumes, preferably in 3D, to extract different cell types. An optimal labeling tool and strategy will be selected to facilitate the segmentation process. Considering that data from µCT scans are inherently noisy, an essential aspect of this research is to determine an optimal denoising strategy .
In the subsequent step, we aim to identify specific structures within the wood samples that allow for accurate assignment to a particular tree species or genus. Due to the limited number of CT volumes available, techniques will be employed to virtually increase the dataset’s size. Furthermore, considering the distinct anatomical characteristics of wood in different cutting directions (axial, lateral, and radial), the orientation of the wood samples will be considered and detected for more accurate identification.
Some of the salient features that can be identified through µCT systems include the distinction between scattered-pored woods (e.g., beech, birch, maple) and ring-pored woods (e.g., oak, elm, ash) based on pore structure, as well as the structure and number of resin canals in conifers. Additionally, other features, such as the shape of the tracheid and the number of rays, contribute to the clear identification of wood samples.
Through this research, we aim to establish a robust framework for wood identification using micro-CT, paving the way for future applications in identifying tropical timber from µCT scans of timber samples. The potential of this method lies in its ability to complement DNA-based wood identification and offer a comprehensive approach to verify the origin of timber and combat illegal logging effectively.
 Jiao, L., Lu, Y., He, T., Guo, J., & Yin, Y. (2020). DNA barcoding for wood identification: global review of the last decade and future perspective, IAWA Journal, 41(4), 620-643.
 Steppe, K., Cnudde, V., Girard, C., Lemeur, R., Cnudde, J. P., & Jacobs, P. (2004). Use of X-ray computed microtomography for non-invasive determination of wood anatomical characteristics. Journal of structural biology, 148(1), 11–21.
 Ghani, M. U., Ren, L., Wong, M., Li, Y., Zheng, B., Rong, X. J., Yang, K., & Liu, H. (2017). Noise Power Characteristics of a Micro-Computed Tomography System. Journal of computer assisted tomography, 41(1), 82–89.
 Haag, V., Dremel, K., & Zabler, S. (2022). Volumetric imaging by micro computed tomography: a suitable tool for wood identification of charcoal, IAWA Journal, 44(2), 210-224.
 Applications in the scope of anatomical wood identification using sub-µCt based volumetric images. In: IUFRO Div 5 Conference: The forest treasure chest: delivering outcomes for everyone; 4-8 June 2023, Cairns, Australia.