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Another application for wood fibres that has recently gained interest is wood polymer composite materials. The properties of these materials do not only depend on the structure of the fibre network, but also on the interaction between the fibres and the polymer matrix surrounding the fibres.
Advances in imaging technology have made it possible to acquire 3D images of paper and wood polymer composite materials. In this project, image analysis methods for characterizing the 3D material structure in such images are developed. The detailed knowledge of the material structure attainable with these methods is useful for improving material properties and for developing new materials.
The project objective is to achieve a complete segmentation of individual fibres and pores in volume images of the material. Given such a segmentation, any desired measurement of the internal structure is available. Measurements on individual fibres and the structural arrangement of fibres can then be related to macroscopic material properties.
In this project, different volume images of paper and composite materials are available: one volume created from a series of 2D scanning electron microscopy (SEM) images at StoraEnso, Falun; and X-ray microtomography volume images of paper and composite samples imaged at the European Radiation Synchrotron Facility (ESRF) in Grenoble, France, at the Paul Scherrer Institut (PSI) in Villigen, Switzerland and during 2010 we have acquired several data with a tabletop scanner at University of Jyväskylä, Finland.
During 2010 further development of methods for de-noising of the
acquired image volumes was undertaken. A variational approach,
minimizing the image Total Variation by Spectral Conjugate Gradient
optimization, showed to outperform previously used SUSAN
filtering. The developed model for generating synthetic µCT
data facilitated objective performance
comparison. Results of this study were presented at the International
Conference on Pattern Recognition (ICPR) in August 2010 and some examples can be seen in Fig.
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So far, the project has resulted in a method to generate and pack
synthetic wood fibres, and a software simulation of the µCT
acquisition system that is capable of reproducing characteristic
artifacts, see Fig, .
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We have developed a method that automatically segments and measures
different attributes of wood fibers from fluorescence microscope
images of compression wood cross-sections. The results were compared
to manual segmentations defined by experts. Fig. shows an example for the automatic and manual delineation. The outer two segmentations lines (see Fig. (a) and (c)) agreed to a satisfying degree. For the inner segmentation line (separating lumen and cell wall) the automatic
method set the boundary slightly further inward compared to the manual
delineation. This caused an systematic error which can be corrected
for. Descriptions of the algorithms and experiments were submitted for
journal publication.
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The images used are log end images of Norway spruce (Picea abies (L.) H.Karst) and Scots pine (Pinus sylvestris L.) captured in a sawmill environment. Logs are sawn with a regular harvester or chainsaw and stored for various times before imaging. The end faces are depicted using either a system camera or an a camera more suitable for industrial applications mounted at the measurement station at Setra Group Nyby sawmill.
End face features are generated according to the procedure of tree growth, including annual rings, knots, heartwood and bark. Also other features are simulated, such as unevenness and roughness from harvesting, camera setup, illumination, and imaging, including colour noise due to Bayer filtering.