SICE Journal of Control, Measurement, and System Integration (Dec 2023)

3D shape reconstruction of Japanese traditional puppet head from CT images by graph cut and machine learning methods

  • Hinata Ikeda,
  • Hiroyuki Ukida,
  • Kouki Yamazoe,
  • Masahide Tominaga,
  • Tomoyo Sasao,
  • Kenji Terada

DOI
https://doi.org/10.1080/18824889.2023.2185929
Journal volume & issue
Vol. 16, no. 1
pp. 117 – 139

Abstract

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In this study, we discuss the digital archiving of Japanese traditional puppets. We propose two methods for extracting the puppet head shape from computed tomography (CT) images. The first is the graph cut method, and the second is a machine learning method based on U-Net. According to the experimental results of the extraction of puppet heads from CT images, the U-Net-based method can extract puppet heads more accurately than the graph cut method. Moreover, the U-Net-based method can extract puppet heads with multiple materials. However, the extraction of metal parts is inaccurate because of metal artefacts in the X-ray CT images and insufficient learning data.

Keywords