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Automatic Measured Drawing Generation for Mokkan Using Deep Learning

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Frontiers of Computer Vision (IW-FCV 2024)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 2143))

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Abstract

This research proposes a method that automatically generates measured drawings for mokkan (wooden strips) using deep-learning technology. The proposed method inputs an image containing one strip of mokkan captured by smartphone or tablet cameras and outputs a measured drawing for the input image. This report details the proposed deep-learning-based method and the dataset collected for training and evaluation of the proposed method. The performance of the proposed method has been empirically confirmed using 337 images of real mokkan. The proposed method has several contributions that promote historical research of mokkan.

This research was supported by JSPS KAKENHI Grant Number JP18H05221.

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Notes

  1. 1.

    The image and annotation dataset of 200 processed mokkan is available at the following address: https://repository.nabunken.go.jp/dspace/handle/11177/7944. Also, the web application of the proposed method is published at the following address: https://ohym.org/MokumeDemo/index_e.html.

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Correspondence to Wataru Ohyama .

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Ohyama, W., Hatano, Y., Baba, H. (2024). Automatic Measured Drawing Generation for Mokkan Using Deep Learning. In: Irie, G., Shin, C., Shibata, T., Nakamura, K. (eds) Frontiers of Computer Vision. IW-FCV 2024. Communications in Computer and Information Science, vol 2143. Springer, Singapore. https://doi.org/10.1007/978-981-97-4249-3_4

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  • DOI: https://doi.org/10.1007/978-981-97-4249-3_4

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-97-4248-6

  • Online ISBN: 978-981-97-4249-3

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