Research on the Qin bamboo slip character images inpainting algorithm based on the context encoder model

Huijuan Chen; Bingquan Chen; Junyi Tan; Bo Jing

doi:10.1117/12.3044958

9 October 2024 Research on the Qin bamboo slip character images inpainting algorithm based on the context encoder model

Huijuan Chen, Bingquan Chen, Junyi Tan, Bo Jing

Proceedings Volume 13288, Fourth International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2024); 132880V (2024) https://doi.org/10.1117/12.3044958
Event: Fourth International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2024), 2024, Chengdu, China

Abstract

In China, through investigation, it has been determined that Qin bamboo slips unearthed as artifacts are severely damaged, deformed, and corroded. The sluggish advancement in Qin bamboo slip inpainting has prompted the exploration of artificial intelligence applications in the domain of image text, offering a promising avenue for the automated restoration of ancient texts. This paper proposes an improved context encoder to restore missing parts in the Qin bamboo slip character images. An encoder can be used to process images, while another encoder can handle text problems, and the encoded representations from both can be combined to generate answers. Additionally, in generative adversarial networks, using two encoders can enhance the performance of both the generator and discriminator, improving training stability. While one encoder encodes the input data into latent space, the discriminator employs the other encoder to improve discrimination between real and generated samples, thereby elevating generation quality and training stability.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Huijuan Chen, Bingquan Chen, Junyi Tan, and Bo Jing "Research on the Qin bamboo slip character images inpainting algorithm based on the context encoder model", Proc. SPIE 13288, Fourth International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2024), 132880V (9 October 2024); https://doi.org/10.1117/12.3044958

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available