論文

査読有り 筆頭著者 責任著者
2015年12月

Automated recognition of wood used in traditional Japanese sculptures by texture analysis of their low-resolution computed tomography data

JOURNAL OF WOOD SCIENCE
  • Kayoko Kobayashi
  • ,
  • Masanori Akada
  • ,
  • Toshiyuki Torigoe
  • ,
  • Setsuo Imazu
  • ,
  • Junji Sugiyama

61
6
開始ページ
630
終了ページ
640
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1007/s10086-015-1507-6
出版者・発行元
SPRINGER JAPAN KK

The identification of wood species used in the cultural artifacts is important in terms of their preservation and inheritance. However, a nondestructive method is required, and wood samples must be partly cut off in conventional methods such as microscopy. In this study, we constructed a novel system for wood identification using image recognition of X-ray computed tomography images of eight major species used in Japanese wooden sculptures. Texture analyses of the computed tomography images were carried out using the gray-level co-occurrence matrix, from which 15 textural features were calculated. The k-nearest-neighbor algorithm combined with cross validation was applied for classification and evaluation of the system. Input datasets with a variation in image qualities (resolution, gray level, and image size) were investigated using this novel system, and the accuracy was greater than 98 % when the input images had a certain quality level. Although there are still technical problems to be overcome, progress in the development of automated identification is extremely encouraging in that such an approach has the potential to make a valuable contribution in adding scientific species notion to the artifacts; otherwise, only the literal documents are available.

リンク情報
DOI
https://doi.org/10.1007/s10086-015-1507-6
J-GLOBAL
https://jglobal.jst.go.jp/detail?JGLOBAL_ID=201502208782108026
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000365710800011&DestApp=WOS_CPL
URL
http://jglobal.jst.go.jp/public/201502208782108026
ID情報
  • DOI : 10.1007/s10086-015-1507-6
  • ISSN : 1435-0211
  • eISSN : 1611-4663
  • J-Global ID : 201502208782108026
  • Web of Science ID : WOS:000365710800011

エクスポート
BibTeX RIS