SwinGAN: a generative adversarial network-based algorithm for generating Qin bamboo slips character images

Ming Chen; Bingquan Chen; Rong Xia; Huijuan Chen; Junyi Tan; Bo Jing

doi:10.1117/12.3017311

15 December 2023 SwinGAN: a generative adversarial network-based algorithm for generating Qin bamboo slips character images

Ming Chen, Bingquan Chen, Rong Xia, Huijuan Chen, Junyi Tan, Bo Jing

Author Affiliations +

Proceedings Volume 12971, Third International Conference on Optics and Communication Technology (ICOCT 2023); 129710S (2023) https://doi.org/10.1117/12.3017311
Event: Third International Conference on Optics and Communication Technology (ICOCT 2023), 2023, Changchun, China

Abstract

This paper presents a generative adversarial network (GAN)-based algorithm for generating Qin bamboo slips character images, specifically addressing the issues of limited samples and a high occurrence of fragmented characters. To mitigate the interference caused by the image background on the network, a global thresholding binary segmentation method is employed to separate the foreground and background of Qin bamboo slips character images. Additionally, we propose the SwinGAN network model based on the DCGAN architecture. The SwinGAN generator network incorporates a windowed multi-head attention mechanism and a Qin Transformer module that combines convolutional neural networks. To prevent gradient varnish, spectral normalization is applied to the convolutional layers of the discriminator, constraining the weight variations. Furthermore, to ensure stable model training, the Wasserstein distance is adopted as the objective function to measure the difference between the generated data distribution and the real data distribution.

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

Citation Download Citation

Ming Chen, Bingquan Chen, Rong Xia, Huijuan Chen, Junyi Tan, and Bo Jing "SwinGAN: a generative adversarial network-based algorithm for generating Qin bamboo slips character images", Proc. SPIE 12971, Third International Conference on Optics and Communication Technology (ICOCT 2023), 129710S (15 December 2023); https://doi.org/10.1117/12.3017311

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