Detection of wood species and defects with NIR

In this project the possibility to determine different wood species and detect defects on wood cross-sections on logs with hyperspectral near-infrared camera was investigated. This project was a laboratory study where cross-sections of logs were scanned at the wood and fibre analysis laboratory at RISE with near-infrared instrument.Wood samples from different origins and species, with different defects were scanned with a hyperspectral near-infrared camera. Classification models were developed to characterise and classify the different logs.Spruce and pine samples were collected from different sawmills, a group of these samples contained fungal growth. The defects within the collected logs varied and some samples contained decay fungi such as sap- and heart rot as well as non-destructive blue stain. Classifications models to distinguish between different wood species were developed, as well classification models to differentiate between healthy wood and the fungal attack were also developed.

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