A digital image credibility evaluation model based on encoder-decoder network

Xiaoyu Chen; Ming Lu; Qin Mao

doi:10.1117/12.3026175

8 April 2024 A digital image credibility evaluation model based on encoder-decoder network

Xiaoyu Chen, Ming Lu, Qin Mao

Proceedings Volume 13090, International Conference on Computer Application and Information Security (ICCAIS 2023); 130901F (2024) https://doi.org/10.1117/12.3026175
Event: International Conference on Computer Application and Information Security (ICCAIS 2023), 2023, Wuhan, China

Abstract

The existing research on digital image forensics at home and abroad provides certain technical support for the authenticity appraisal of digital images. However, most users have not fully examined the difference between the normal processing of digital images and malicious tampering behavior, which not only stifles the normal processing of digital images such as beautification and polishing, but also hinders the development of digital image processing technology and the promotion of corresponding software. This means that it is not only about simply detecting whether the image has been processed but also interpreting and evaluating the detected processing in conjunction with the image content. Based on the user’s needs for normal image processing, and considering the difference in the authenticity of the image content before and after processing as the standard, correctly distinguishing between normal user modification and malicious tampering, is different from existing digital image forensics technology. This article proposes a digital image authenticity evaluation model based on an encoder-decoder network, which utilizes deep learning techniques to extract relevant features of digital images and construct an authenticity evaluation model. The encoder-decoder network is used to comprehensively evaluate whether the semantic information of digital images is true and trustworthy, thus avoiding misjudgment of authenticity. Finally, the effectiveness of the proposed digital image authenticity authentication model was verified through experiments.

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

Citation Download Citation

Xiaoyu Chen, Ming Lu, and Qin Mao "A digital image credibility evaluation model based on encoder-decoder network", Proc. SPIE 13090, International Conference on Computer Application and Information Security (ICCAIS 2023), 130901F (8 April 2024); https://doi.org/10.1117/12.3026175

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KEYWORDS

Image processing

Digital image processing

Digital imaging

Image forensics

Image analysis

Digital forensics

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