Abstract
Computed Tomography (CT) is extensively used as a medical diagnostic tool, and increasingly for scientific and industrial research. In the wood industry, there is a growing interest in using the CT technique to assess the quality of logs entering a sawmill. Internal features of interest include knots, heartwood/sapwood boundary, rot and splits. Most commercially available CT scanning systems are modeled on medical designs and provide high spatial and density resolution. However, they are very complex and delicate devices and their cost is correspondingly high. So far, there is no commercially available CT scanner that can meet the extreme scanning speed requirement, moderate affordability and severe working environment in a sawmill. To address these challenges for using CT technology for industrial log scanning, a novel coarse-resolution cone-beam CT scanning system has been developed. To accommodate the modestly accurate log transport systems in sawmills and hence address the substantial associated lateral motions, an Eulerian approach is taken whereby the CT reconstruction is based on the moving log rather than on the fixed space traversed by the log. This paper, the first of a two-part report, describes a novel cone beam scanning concept, geometry-based coarse-resolution log models, customized CT data processing, normalization and efficient cone beam reconstruction algorithms. The second part of this report will describe the construction details and practical performance of a prototype device.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Oja J, Grundberg S, Fredriksson J, Berg P (2004) Automatic grading of sawlogs: a comparison between X-ray scanning optical three-dimensional scanning and combinations of both methods. Scand J Forest Res 19:89–95
Pietkäininen M (1996) Detection of knots in logs using X-ray imaging. Dissertation, Technical Research Centre of Finland, Espoo, VTT Publications 266
Usenius A (2003). Optimization of sawing operation based on internal characterization of the logs. In: Proceedings ScanTech 2003, Wood Machining Institute, Seattle, pp 11–18
Rinnhofer A, Petutschnig A, Andreu JP (2003) Internal log scanning for optimizing breakdown. Comput Electron Agric 41:7–21
Chiorescu S, Grönlund A (2000) Validation of a CT-based simulator against a sawmill yield. Forest Prod J 50:69–76
Oja J, Wallbacks L, Grundberg S, Hagerdal E, Grönlund A (2003) Automatic grading of Scots pine (Pinus sylvestris L.) sawlogs using an industrial X-ray log scanner. Comput Electron Agric 41:63–75
Seger MM, Danielson PE (2003) Scanning of logs with linear cone-beam tomography. Comput Electron Agric 41:45–62
Lindgren LO (1991) Medical CAT-scanning X-ray absorption coefficients, CT-number and their relation to wood density. Wood Sci Technol 25:341–349
Som S, Wells P, Davis J (1992) Automated feature extraction of wood from tomographic images. In: Proceeding of international conference on automation, robotics and computer vision, Singapore, 15–18 Sept 1992, pp CV-14.4.1–CV-14.4.5
Krahenbuhl A, Kerautret B, Longuetaud F (2011) Knots detection in X-ray CT images of wood. Scand J Forest Res 12:80–90
Longuetaud F, Mothe F, Kerautret B (2012) Automatic knots detection and measurements from X-ray CT images of wood: a review and validation of an improved algorithm on softwood samples. Comput Electron Agric 85:77–89
Wang G, Yu H (2008) An outlook on X-ray CT research and development. Med Phys 35(3):1051–1064
Kak AC, Slaney M (1987) Principles of computerized tomography. IEEE Press, New York
ASTM (1993) Standard guide for computed tomography (CT) imaging. American Society for Testing and Materials, West Conshohocken. ASTM Standard E-1441-11, 33pp
Galassi M et al (2009) GNU scientific library reference manual, 3rd edn. http://www.gnu.org/software/gsl/. Accessed 25 June 2011
Acknowledgments
The authors gratefully thank the Natural Science and Engineering Research Council of Canada (NSERC) for their financial support of this project through the ForValueNet network, the Centre for Hip Health and Mobility, Vancouver General Hospital, for use of facilities, and the Institute for Computing, Information and Cognitive Systems (ICICS).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 The Society for Experimental Mechanics, Inc.
About this paper
Cite this paper
An, Y., Schajer, G.S. (2014). Coarse-Resolution Cone-Beam Scanning of Logs Using Eulerian CT Reconstruction. Part I: Discretization and Algorithm. In: Rossi, M., et al. Residual Stress, Thermomechanics & Infrared Imaging, Hybrid Techniques and Inverse Problems, Volume 8. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-319-00876-9_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-00876-9_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-00875-2
Online ISBN: 978-3-319-00876-9
eBook Packages: EngineeringEngineering (R0)