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< 구두-B-02 > Visualizing MFA distribution from cross-section of wood cell wall
( Yusuke Kita ),( Junji Sugiyama ) 한국목재공학회 2019 한국목재공학회 학술발표논문집 Vol.2019 No.1
The orientation angle of the microfibril along the longitudinal axis of the plant cell wall, microfibril angle (MFA), is considered as one of the most important indices because of its obvious correlation with the mechanical and chemical properties of the plant itself like Young’s modulus, shrinkage anisotropy and so on. Therefore, many ways have been invented to estimate the MFA values. However, most of the conventional methods only give us the limited information, local or spatial mean MFA values. Hence, the brand-new approach is needed which can access microscopic and macroscopic MFA values simultaneously. This study proposes the technique for evaluating the MFA distribution from the cross section of wood cell wall by use of optical anisotropy of cellulose microfibril. 10μm cross sections of 3 wood species (C. obtusa, T. dolabrata, T. cuspidata) were prepared by sliding microtome. Wavelength-sliced images among 460-601 nm under the polarization with sensitive color plate (λ= 530 nm) were extracted by polarization optical microscope (Olympus Inc.) and VariSpec liquid crystal tunable filter (CRi Inc.). The magnification of the objective lens and the interval of the sliced images were set to x10 and 3nm, respectively. Finally, these images were sequentially transformed into light intensity profiles, retardation (nm) and MFA (degree) values, respectively. This methodology reveals the potential for visualizing 2-dimensional qualitative MFA distribution in the wide range at a one time.
( Takeshi Nakajima ),( Kayoko Kobayashi ),( Junji Sugiyama ) 한국목재공학회 2019 한국목재공학회 학술발표논문집 Vol.2019 No.1
Tree-ring analysis is an important field of science, including dendrochronology, dendroclimatology and modeling the tree growth environmental response system. In most cases the analyses have been conducted using one parameter from one tree-ring, e.g. ring-width, density, ratio of radioisotope, and so on. The information within a ring, however, has been less studied and many more things to be explored such as seasonal response in the shorter time scales. From another point of view, many species of softwood are often used into tree-ring analyses but our previous work revealed that simple CNN models did not work well in identification of softwood images where the morphology is rather regular or periodic. Therefore, substantial improvement in either feature extraction or the design of neural network was needed. In this study, therefore, we applied wavelet transform into deep-learning technique in order to extract information of tree growth environmental response in sub-seasonal time scales from softwood images.
( Sung-wook Hwang ),( Kayoko Kobayashi ),( Junji Sugiyama ) 한국목재공학회 2019 한국목재공학회 학술발표논문집 Vol.2019 No.1
A bag-of-features (BOF) model was implemented to further investigate the Lauraceae family through computer vision techniques. The key function of the BOF is to represent an image as a histogram using a codebook (or visual words) generated by clustering of detected features from images. Local features extracted by the scale-invariant feature transform (SIFT) algorithm were used to generate a codebook. In our previous study, it was confirmed that the SIFT keypoints have a high discriminant power in wood classification. In the proposed model, 1019 cross-sectional optical micrographs of 9 species across 6 genera from the Lauraceae family are tested. The visual words can be further analyzed by mapping them to each image to visualize the corresponding anatomical features. From such analysis, the computer vision technique can classify the aggregation of different combinations of wood cells such as vessels, wood fibers, rays, and axial parenchyma cells. The term frequency-inverse document frequency weights reveals that cell corner-based features are more species specific than cell lumen-based features. The codebook-based wood recognition model allowed us to approach the classification problem of wood based on the domain knowledge of wood anatomy.
( Sung-wook Hwang ),( Suyako Tazuru ),( Junji Sugiyama ) 한국목재공학회 2020 목재공학 Vol.48 No.3
For visual inspection-based wood identification, optical microscopy techniques typically require a relatively large sample size, and a scanning electron microscope requires a clean surface. These novel techniques experience limitations for objects with highly limited sampling capabilities such as important and registered wooden cultural properties. Synchrotron X-ray microtomography (SR-μCT) has been suggested as an effective alternative to avoid such limitations and various other imaging issues. In this study, four pieces of wood fragments from wooden members used in the Manseru pavilion of Bongjeongsa temple in Andong, Korea, wereused for identification. Three-dimensional microstructural images were reconstructed from these small wood samples using SR-μCT at SPring-8. From the analysis of the reconstructed images, the samples were identified as Zelkova serrata, Quercus sect. Cerris, and Pinus koraiensis. The images displayed sufficient spatial resolution to clearly observe the anatomical features of each species. In addition, the three-dimensional imaging allowed unlimited image processing.