Chinese font translation with improved Wasserstein generative adversarial network

Yalin Miao; Huanhuan Jia; Kaixu Tang; Yichun Ji

doi:10.1117/12.2559366

31 January 2020 Chinese font translation with improved Wasserstein generative adversarial network

Yalin Miao, Huanhuan Jia, Kaixu Tang, Yichun Ji

Proceedings Volume 11433, Twelfth International Conference on Machine Vision (ICMV 2019); 114333O (2020) https://doi.org/10.1117/12.2559366
Event: Twelfth International Conference on Machine Vision, 2019, Amsterdam, Netherlands

Abstract

Nowadays, various fonts are applied in many fields, and the generation of multiple fonts by computer plays an important role in the inheritance, development and innovation of Chinese culture. Aiming at the existing font generation methods, which have some problems such as stroke deletion, artifact and blur, this paper proposes Chinese font translation with improved wasserstein generative adversarial network. The wasserstein distance is used to measure distance and difference between the two distributions, and the gradient penalty mechanism is used instead of the weight clipping. The residual dense blocks with better flexibility are selected as the core component to extract the features fully and enhance the information transmission between network layers. It realizes the style migration between different Chinese fonts. Experiments show that the proposed method has better performance in font generation details, simplifies the font translation process, and improves the fidelity of font generation.

Citation Download Citation

Yalin Miao, Huanhuan Jia, Kaixu Tang, and Yichun Ji "Chinese font translation with improved Wasserstein generative adversarial network", Proc. SPIE 11433, Twelfth International Conference on Machine Vision (ICMV 2019), 114333O (31 January 2020); https://doi.org/10.1117/12.2559366

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available