<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>As a classic representative of traditional culture, Chinese calligraphy art has more and more obvious advantages in today’s digital media art creation. In this paper, the calligraphic text image is binarized by the OTSU method, the image enhancement is realized by linear gray value stretching, and the optimal tilt correction method is used to preprocess the traditional calligraphic text image and make a font library. Based on the data from the calligraphy font library, an immersive digital interactive context of traditional calligraphy is designed using digital media art. Pix2Pix network is introduced to combine with the PatchGAN network to establish a style migration network for traditional calligraphy text images, and three different types of loss functions are designed to ensure the accurate generation of traditional calligraphy text. The L1 loss of this paper’s model in generating traditional calligraphy characters is only 0.0359 at the lowest, the similarity values of the generated samples of calligraphy characters are mainly between 90% and 96%, and the maximum error of the relative position and relative size of the radicals is only 1.18%. The average value of the G2R indicator for the users’ images of calligraphic characters was 75.23%, and 89.86% of the users indicated that they were basically satisfied with the immersive interactive context of traditional calligraphy. Traditional calligraphy can achieve digital transformation and provide audiences with more diverse cultural experiences by relying on digital media art.</p>
</abstract>

As a classic representative of traditional culture, Chinese calligraphy art has more and more obvious advantages in today’s digital media art creation. In this paper, the calligraphic text image is binarized by the OTSU method, the image enhancement is realized by linear gray value stretching, and the optimal tilt correction method is used to preprocess the traditional calligraphic text image and make a font library. Based on the data from the calligraphy font library, an immersive digital interactive context of traditional calligraphy is designed using digital media art. Pix2Pix network is introduced to combine with the PatchGAN network to establish a style migration network for traditional calligraphy text images, and three different types of loss functions are designed to ensure the accurate generation of traditional calligraphy text. The L1 loss of this paper’s model in generating traditional calligraphy characters is only 0.0359 at the lowest, the similarity values of the generated samples of calligraphy characters are mainly between 90% and 96%, and the maximum error of the relative position and relative size of the radicals is only 1.18%. The average value of the G2R indicator for the users’ images of calligraphic characters was 75.23%, and 89.86% of the users indicated that they were basically satisfied with the immersive interactive context of traditional calligraphy. Traditional calligraphy can achieve digital transformation and provide audiences with more diverse cultural experiences by relying on digital media art.

A Study of the Intersection of Traditional Calligraphy and Digital Media Art

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"A Study of the Intersection of Traditional Calligraphy and Digital Media Art"}

As a classic representative of traditional culture, Chinese calligraphy art has more and more obvious advantages in today’s digital media art creation. In this...

A Study of the Intersection of Traditional Calligraphy and Digital Media Art

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 16. Apr. 2024

Akzeptiert: 04. Juli 2024

DOI: https://doi.org/10.2478/amns-2024-2148

Schlüsselwörter
OTSU method, Tilt correction, Pix2Pix network, PatchGAN, Style migration, Traditional calligraphy

© 2024 Peijun Xiong, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

A Study of the Intersection of Traditional Calligraphy and Digital Media Art

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 16. Apr. 2024

Akzeptiert: 04. Juli 2024

DOI: https://doi.org/10.2478/amns-2024-2148

SchlüsselwörterOTSU method, Tilt correction, Pix2Pix network, PatchGAN, Style migration, Traditional calligraphy

© 2024 Peijun Xiong, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
OTSU method, Tilt correction, Pix2Pix network, PatchGAN, Style migration, Traditional calligraphy