Style Transfer Technology of Batik Pattern Based on Deep Learning

Style Transfer Technology of Batik Pattern Based on Deep Learning

Year:    2023

Author:    Jing Zhang, Yan Jiang

Journal of Fiber Bioengineering and Informatics, Vol. 16 (2023), Iss. 1 : pp. 57–67

Abstract

AI painting has recently come into public view, improving the efficiency of users' creations. At present, the research and application of popular products such as characters and landscapes are more, but the research of Miao batik patterns is lacking. Therefore, this paper studies the style transfer of batik patterns from two aspects. First, a local style transfer model of batik patterns with enhanced edges is proposed. The loss function is composed of local content loss, local style loss and Laplacian loss, and the generated images have good performance in detail texture and color space. The other is to use the existing model in the AI painting tool Stable Diffusion for style transfer of batik patterns. It performs well in running time and memory occupation, but the generated image cannot inherit the style and content images well in color and detail.

You do not have full access to this article.

Already a Subscriber? Sign in as an individual or via your institution

Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.3993/jfbim02171

Journal of Fiber Bioengineering and Informatics, Vol. 16 (2023), Iss. 1 : pp. 57–67

Published online:    2023-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    11

Keywords:    Style Transfer

Author Details

Jing Zhang

Yan Jiang