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Institute of

HF Wood Research


Automated image recognition for wood species identification

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Development of automated (digital) image recognition systems for wood species identification using artificial intelligence

Can wood species be identified with absolute certainty by means of machine learning?
We are working on this question in the FNR project in collaboration with the Fraunhofer Institute. The aim: automated image recognition systems for wood species identification.

Background and Objective

In order to strengthen the trade with legal raw materials and to protect consumers, the used wood species are determined at the Thünen Centre of Competence on the Origin of Timber. Cut specimens of wood and, in the case of fibrous materials such as paper, individual cells are routinely examined under a light microscope and analyzed by experts at great expense of time. Automated image recognition systems can save an enormous amount of work and time here.

With the introduction of the European Timber Regulation (EUTR) in 2013, the trade is obliged to document, among other things, the type of wood contained in the product in order to ensure its legal origin. Within the framework of the new research project, automated image recognition systems using artificial intelligence (AI) are to be developed in order to be able to check the wood species declaration of the manufacturers on a larger scale.

The Fraunhofer Institute ITWM is contributing its expertise by developing the specific algorithms and training the software using machine learning. The results are to be published scientifically and provided to all testing institutes for the control of internationally traded wood.

Target Group

Authorities, science, timber trade and consumers


For a selection of relevant hardwoods, samples from the scientific collection and other documented sources are processed into realistic training and test specimens. In the slide scanning microscope specially acquired for this project, 100 slides can be inserted simultaneously. Automated microscopic images are then taken in multiple focal planes over the entire slide area. These images represent the important data basis of the project. In these images, the cells that are essential for the identification of the wood genus by wood anatomists are labeled. Machine learning systems are trained and validated with these at the ITWM.

Our Research Questions

Is it possible to identify wood species with machine learning?

Links and Downloads

Involved external Thünen-Partners

  • Fraunhofer-Institut für Techno- und Wirtschaftsmathematik ITWM
    (Kaiserslautern, Deutschland)

Funding Body

  • Fachagentur Nachwachsende Rohstoffe e.V. (FNR)
    (national, öffentlich)


6.2021 - 5.2024

More Information

Project funding number: 2220HV063A
Project status: ongoing

Mikroskopische Aufnahmen von Gefäßelementen der Gattung Betula und Eucalyptus (© Thünen-Institut)

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