Paper
16 September 1999 Woodmetrics: imaging devices and processes in wood inspection at Lulea University of Technology
Olle Hagman
Author Affiliations +
Proceedings Volume 3826, Polarization and Color Techniques in Industrial Inspection; (1999) https://doi.org/10.1117/12.364320
Event: Industrial Lasers and Inspection (EUROPTO Series), 1999, Munich, Germany
Abstract
Wood Technology research and education at Lulea University of Technology is located in Skelleftea 800 km north of Stockholm. At the campus about 25 persons are involved in education and research in Wood Technology. We are educating M.Sc. and post- graduate students in Wood Technology. The research at the campus includes the following main fields: -- Wood Machining - - Woodmetrics -- Wood Drying -- Wood Composites/Wood Material Science. Our research strategy is to obtain an individual treatment of every tree, board and piece of wood in order to get highest possible value for the forest products. This shall be accomplished by the aid of advanced scanning technology and computer technology. Woodmetrics means to measure different wood parameters in order to optimize the utilization of the raw material. Today we have the following projects in this field: Automatic wood inspection -- Color changes and moisture flow in drying processes -- Inner quality of logs and lumber - - Stem quality database -- Computer tomography -- Aesthetic properties of wood -- Market/industry/forest relations. In the Woodmetrics field we are using computer tomography, CCD cameras and other sensors in order to find and measure defects in trees and on boards. The signals are analyzed and classified with modern image analyzing techniques and advanced statistical methods.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Olle Hagman "Woodmetrics: imaging devices and processes in wood inspection at Lulea University of Technology", Proc. SPIE 3826, Polarization and Color Techniques in Industrial Inspection, (16 September 1999); https://doi.org/10.1117/12.364320
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KEYWORDS
Sensors

Computed tomography

Data modeling

Inspection

Reflection

Image analysis

Image sensors

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