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Texture Analysis of Stereograms of Diffuse-Porous Hardwood: Identification of Wood Species Used in Tripitaka Koreana

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Author(s)
Kobayashi, Kayoko
Hwang, Sung-Wook
Lee, Won-Hee
Sugiyama, Junji
Contributor(s)
小林, 加代子
杉山, 淳司
Keywords
Image recognition
Stereogram
Texture analysis
Tripitaka Koreana
Wood identification

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URI
http://hdl.handle.net/20.500.12424/2134609
Online Access
http://hdl.handle.net/2433/230921
Abstract
Tripitaka Koreana is a collection of over 80, 000 Buddhist texts carved on wooden blocks. In this study, we investigated whether six hardwood species used as blocks could be recognized by image recognition. An image dataset comprising stereograms in transverse section was acquired at 10× magnification. After auto-rotation, cropping, and filtering processes, the dataset was analyzed by an image recognition system, which comprised a gray level co-occurrence matrix method for feature extraction and a weighted neighbor distance algorithm for classification. The estimated accuracy obtained by leave-one-out cross-validation was up to 100% after optimizing the pretreatments and parameters, thereby indicating that the proposed system may be useful for the non-destructive analysis of all wooden carvings. We also examined the specific anatomical features represented by textures in the images. Many of the texture features were apparently related to the density of vessels and others were associated with the ray intervals. However, some anatomical features that are helpful for visual inspection were ignored by the proposed system despite its perfect accuracy. In addition to the high analytical accuracy of this system, a deeper understanding of the relationships between the calculated and actual features is essential for the further development of automated recognition.
Date
2018-05-01
Type
Journal Article
Identifier
oai:repository.kulib.kyoto-u.ac.jp:2433/230921
1435-0211
http://hdl.handle.net/2433/230921
Journal of Wood Science
63
4
322
330
25252033
Copyright/License
© The Author(s) 2017. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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