Title: AI-based artist style appreciation: folk art in the central plains oriented implementation platform

Authors: Wei Tian

Addresses: Henan Institute of Science and Technology, Henan, Xinxiang, China

Abstract: The folk art in the Central Plains is rich in variety and has strong vitality. The culture of the Central Plains has a long history, and folk art is considered to be a representative type of folk culture in the Central Plains. However, there are few platforms for appreciation of folk-art styles. Therefore, based on the artificial intelligence technology that has been in the forefront of science and technology in recent years, image style transfer is used to guide the appreciators to appreciate the folk-art resources of Central Plains from multiple perspectives. Given this, this study proposes an image of folk art in the Central Plains style transfer algorithm with salient region reservation by fast style transfer algorithm. By introducing saliency detection network to generate saliency map of composite image and content image, which is helpful to improve the quality of stylised image. Experiments show that the stylised image generated by the algorithm proposed in this paper not only has satisfactory colour and texture, but also reserves salient regions in the content image, which is conducive to the appreciation of the folk-art in the Central Plains.

Keywords: folk art; central plains; AI; image style transfer; stylised image.

DOI: 10.1504/IJCAT.2023.132091

International Journal of Computer Applications in Technology, 2023 Vol.71 No.3, pp.181 - 191

Received: 17 Jan 2022
Received in revised form: 09 Mar 2022
Accepted: 12 Mar 2022
Published online: 11 Jul 2023 *

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