3D shape reconstruction of Japanese traditional puppet head from CT images by graph cut and machine learning methods. Issue 1 (31st December 2023)

• Record Type: Journal Article
• Authors: Ikeda, Hinata; Ukida, Hiroyuki; Yamazoe, Kouki; Tominaga, Masahide; Sasao, Tomoyo; Terada, Kenji
• Is Part Of: SICE journal of control, measurement, and system integration. Volume 16:Issue 1(2023)
• Page Start: 117
• Page End: 139
• Publication Date: 2023-12-31
• Subjects: 3D shape reconstruction -- puppet head -- X-ray CT images -- graph cut method -- machine learning -- U-Net
• DOI: 10.1080/18824889.2023.2185929
• Languages: English
• ISSNs: 1882-4889

Abstract

ABSTRACT: 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.