Target segmentation algorithm for Chinese traditional flower-and-bird paintings based on object detection

Xinquan Luo; Yinghui Wang; Zhuwen Zhao; Qingchen Nie

doi:10.1117/12.3008107

14 November 2023 Target segmentation algorithm for Chinese traditional flower-and-bird paintings based on object detection

Xinquan Luo, Yinghui Wang, Zhuwen Zhao, Qingchen Nie

Author Affiliations +

Proceedings Volume 12934, Third International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2023); 129341U (2023) https://doi.org/10.1117/12.3008107
Event: 2023 3rd International Conference on Computer Graphics, Image and Virtualization (ICCGIV 2023), 2023, Nanjing, China

Abstract

Recognizing and segmenting artistic targets in Chinese paintings is an important method for analyzing and studying this art form. In order to enrich the expressive forms and cultural connotations of Chinese paintings, as well as promote the modernization of traditional culture, this paper proposes a segmentation method for animals in Chinese paintings. Firstly, using the Swin Transformer, artistic targets such as animals in Chinese paintings are detected, and the interested target image blocks are cropped. Then, the Attention UNet model is employed to achieve high-precision image segmentation for animals in Chinese paintings. Experimental results demonstrate that our algorithm successfully segments 19 species of animals in the sample dataset, achieving high accuracy and accurately segmenting the artistic targets in Chinese traditional flower-and-bird paintings. The achievements of this paper can be applied to the digital research of Chinese paintings, providing technical references for the inheritance and development of Chinese traditional painting.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xinquan Luo, Yinghui Wang, Zhuwen Zhao, and Qingchen Nie "Target segmentation algorithm for Chinese traditional flower-and-bird paintings based on object detection", Proc. SPIE 12934, Third International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2023), 129341U (14 November 2023); https://doi.org/10.1117/12.3008107

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