Wood Species Dataset with 8,544 Macroscopic Images

8,544 macroscopic images of wood species form this dataset, created by researchers from Imperial College London and Aristotle University of Thessaloniki. The dataset supports wood species recognition through multidimensional texture analysis, as described in a 2018 research paper. It is version 2 of the dataset, with the underlying data archived on Zenodo in 2019.

Use Cases

• Train image classification models for wood species recognition based on macroscopic texture.
• Benchmark texture analysis algorithms using the provided image categories.
• Develop automated quality control systems for timber and wood products based on visual inspection.

Strengths

• Contains 8,544 macroscopic images, providing a substantial visual corpus.
• Associated with a peer-reviewed 2018 research paper in Computers and Electronics in Agriculture.
• Created by researchers from Imperial College London and Aristotle University of Thessaloniki.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

Imperial College London, Aristotle University of Thessaloniki

Collection Method

Likely collected through photographic capture of wood samples.