Mr. Hoshito Minagi Profile

Hoshito Minagi

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Proceedings Article | 1 May 2022 Paper

Study of automatic generation of motif tag in Nishiki-e

Hoshito Minagi, Takuzi Suzuki, Yoshitugu Manabe, Noriko Yata

Proceedings Volume 12177, 1217717 (2022) https://doi.org/10.1117/12.2626097

KEYWORDS: Image segmentation, Photography, Image processing, Composites, Image fusion, Databases, Visualization, Printing, Image registration

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The motif drawn on Nishiki-e is needed to register in the database as a search tag. The accuracies of the motif tag that are currently manually registered is unstable because it depends on the knowledge and interests of the registrant. Therefore, this study proposes an automatic generation method of motif tags using deep learning to support cultural activities. Nishiki-e is more difficult to collect training images that include specific motifs than photographs. In this study, we propose three methods for preparing training images. First, we applied a similar image generation model from a single image to a small number of Nishiki-e containing motifs to create training images. Second, we applied a Nishiki-e style processing model to photographs containing motifs to create training images. Third, we combined a small number of photographs with motifs with some background images to create training images. In particular, the third method can detect from a small number of inputs like the first method with an accuracy close to that of the second method.

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