The technology of dyeing wood by microorganisms is a kind of pollution-free and sustainable wood dyeing technology. To achieve fast and rich dyeing of on the surface of poplar wood, tyrosinase and tricyclazole were used as induction factors in this experiment. The results showed that had a better induction effect in the cross-section of poplar wood and induced with tricyclazole. The surface color of poplar ranged from light yellow dyeing to gray and brown, the chromatic aberration of the cross-section of wood was above 44.5 NBS, and the infected area was over 50%, while the dyed parts of radial and tangential sections of wood were only on the surface of the wood after 30 days of infection. The induced infection of on poplar wood had little effect on the chemical components of poplar and had good colorfastness to washing and light. Therefore, microbial dyeing of wood showed a beneficial application prospect in the field of wood dyeing.

The proof of origin of wood logs is becoming more and more important. In the context of Industry 4.0 and to combat illegal logging, there is an increased interest to track each individual log. There were already previous publications on wood log tracing using image data from logs, but these publications used experimental setups that cannot simulate a practical application where logs are tracked between different stages of the wood processing chain, like e.g. from the forest to the sawmill. In this work, we employ image data from the same 100 logs that were acquired at different stages of the wood processing chain (two datasets at the forest, one at a laboratory and two at the sawmill including one acquired with a CT scanner). Cross-dataset wood tracking experiments are applied using (a) the two forest datasets, (b) one forest and the RGB sawmill dataset and (c) different RGB datasets and the CT sawmill dataset. In our experiments we employ two CNN based method, 2 shape descriptors and two methods from the biometric areas of iris and fingerprint recognition. We will show that wood log tracing between different stages of the wood processing chain is feasible, even if the images at different stages are obtained at different image domains (RGB-CT). But it only works if the log cross sections from different stages of the wood processing chain either offer a good visibility of the annual ring pattern or share the same woodcut pattern.