In several processes of the forest products industry, an in-depth knowledge of log and board internal features is required and their determination needs fast scanning systems. One of the possible technologies is X-ray computed tomography (CT) technology. Our paper reviews applications of this technology in wood density measurements, in wood moisture content monitoring, and in locating internal log features that include pith, sapwood, heartwood, knots, and other defects. Annual growth ring measurements are more problematic to be detected on CT images because of the low spatial resolution of the images used. For log feature identification, our review shows that the feed-forward back-propagation artificial neural network is the most efficient CT image processing method. There are also some studies attempting to reconstruct three-dimensional log or board images from two-dimensional CT images. Several industrial prototypes have been developed because medical CT scanners were shown to be inappropriate for the wood industry. Because of the high cost of X-ray CT scanner equipment, other types of inexpensive sensors should also be investigated, such as electric resistivity tomography and microwaves. It also appears that the best approach uses various different sensors, each of them having its own strengths and weaknesses.
Evaluation of Microstructure and Transport Properties of Deteriorated Cementitious Materials from Their X-ray Computed Tomography (CT) Images
