Journal of Guangdong University of Technology ›› 2019, Vol. 36 ›› Issue (03): 47-55.doi: 10.12052/gdutxb.180162

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A Two-stage Effect Rendering Method for Art Font Based on CGAN Network

Ye Wu-jian1, Gao Hai-jian1, Weng Shao-wei1, Gao Zhi1, Wang Shan-jin2, Zhang Chun-yu3, Liu Yi-jun1   

  1. 1. School of Information Engineering, Guangdong University of Technology, Guangzhou, 510006, China;
    2. School of Electrical Engineering & Intelligentization, Dongguan University of Technology, Dongguan, 523808, China;
    3. School of Information Engineering, Xizang Minzu University, Xianyang, 712082, China
  • Received:2018-11-28 Online:2019-05-09 Published:2019-04-04

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Abstract: Art font rendering is one of the important techniques of media typesetting. How to provide an efficient art font rendering method to realize the diversity and clearness of the special effects of generative art fonts is an urgent problem for technicians in this field. With the help of Conditional Generative Adversarial Networks (CGAN), a two-stage art font rendering method that includes style transfer processing and enhancement processing is proposed to achieve high quality rendering of art fonts. First, by style transfer processing, a stylized network model is built to render various 2D or 3D special effects on a variety of input fonts. Then, by enhancement processing, a sharpening network model is built to sharpen the generated art font images, which overcomes the defect of fuzzy image generation in a single GAN network. The experimental results show that, comparing with existing methods, this scheme has a better performance for generating more diverse and more clear special art fonts, whose texture details are relatively rich, and are not limited to the text skeleton. At the same time, this scheme can also improve the efficiency of art font rendering in the batch processing and has a higher practical value.

Key words: art font, effect rendering, conditional generative adversarial networks, style transfer, sharpness

CLC Number: 

  • TP391
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