Detection of wood species and defects by NIR
This project investigated the possibility of determining different wood species and detecting defects on wood cross-sections of logs using a hyperspectral near-infrared camera. This project was a laboratory study where cross sections of logs were scanned with a near-infrared instrument at the Wood and Fiber Analysis Laboratory at RISE.
Wood samples from different origins and species, with different defects, were scanned with a hyperspectral near-infrared camera. Classification models were developed to characterize and classify the different logs. Spruce and pine samples were collected from different sawmills, and a group of these samples contained fungal attacks. The defects in the collected logs varied, and some samples contained decay diseases such as resin rot and heart rot as well as non-destructive blue stain. Classification models were developed to distinguish different wood species, and classification models to distinguish between healthy wood and fungal attack were also developed.
Area: Materials & Processes
Budget: 387 000 SEK
Time: March 2021 - October2022
Project leader: Thomas Grahn, RISE
Funding: This subproject is funded by TCN.
Updated: