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Calligraphy Z: A Fabricatable Pen Plotter for Handwritten Strokes with Z-Axis Pen Pressure

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Published:28 October 2022Publication History

ABSTRACT

In the current age, the use of desktop publishing software and printing presses makes it possible to produce various expressions. On the other hand, it is difficult to perfectly replicate the ink grazing and subtle pressure fluctuations that occur when using a writing implement to output characters on a printer. In this study, we reproduce such incidental brushstrokes by using a writing implement to output text layout created on software. To replicate slight variations in strokes, we developed Calligraphy Z, a system that consists of a writing device and an application. The writing device controls the vertical position of the writing tool in addition to the writing position, thus producing handwritten-like character output, and an application that generates G-code for the device operation from user input. With the application, users can select their favorite fonts, input words, and adjust the layout to operate the writing device using several types of extended font data with writing pressure data prepared in advance. After developing our system, we compared the strokes of several writing implements to select the most suitable one for Calligraphy Z. We also conducted evaluations of the identification of characters output by Calligraphy Z and those output by a printing machine. We found participants in the evaluation experiment perceive the features of handwritten characters, such as ink blotting and fine blurring of strokes, in the characters by our system.

References

  1. Shohei Katakura, Yuto Kuroki, and Keita Watanabe. 2019. A 3D Printer Head as a Robotic Manipulator. In Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology (New Orleans, LA, USA) (UIST ’19). Association for Computing Machinery, New York, NY, USA, 535–548. https://doi.org/10.1145/3332165.3347885Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Josh Lam and Yeung Yam. 2009. Stroke Trajectory Generation Experiment for a Robotic Chinese Calligrapher Using a Geometric Brush Footprint Model. 2315 – 2320. https://doi.org/10.1109/IROS.2009.5354709Google ScholarGoogle Scholar
  3. Hsien-I Lin, Xuechao Chen, and Tian-Tsai Lin. 2020. Calligraphy Brush Trajectory Control of by a Robotic Arm. Applied Sciences 10 (12 2020), 8694. https://doi.org/10.3390/app10238694Google ScholarGoogle Scholar
  4. Ayaka Matsui and Seiichiro Katsura. 2013. A method of motion reproduction for calligraphy education. In 2013 IEEE International Conference on Mechatronics (ICM). 452–457. https://doi.org/10.1109/ICMECH.2013.6518579Google ScholarGoogle ScholarCross RefCross Ref
  5. Samuel Mueller, Nico Huebel, Markus Waibel, and Raffaello D’Andrea. 2013. Robotic calligraphy — Learning how to write single strokes of Chinese and Japanese characters. In 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems. 1734–1739. https://doi.org/10.1109/IROS.2013.6696583Google ScholarGoogle ScholarCross RefCross Ref

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  1. Calligraphy Z: A Fabricatable Pen Plotter for Handwritten Strokes with Z-Axis Pen Pressure

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    • Published in

      cover image ACM Conferences
      UIST '22 Adjunct: Adjunct Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology
      October 2022
      413 pages
      ISBN:9781450393218
      DOI:10.1145/3526114

      Copyright © 2022 Owner/Author

      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 28 October 2022

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      Overall Acceptance Rate842of3,967submissions,21%

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