Abstract
We propose a high-payload image watermarking method for textual embedding, where a semantic description of the image - which may also correspond to the input text prompt-, is embedded inside the image. In order to be able to robustly embed high payloads in large-scale images - such as those produced by modern AI generators - the proposed approach builds upon a traditional watermarking scheme that exploits orthogonal and turbo codes for improved robustness, and integrates frequency-domain embedding and perceptual masking techniques to enhance watermark imperceptibility. Experiments show that the proposed method is extremely robust against a wide variety of image processing, and the embedded text can be retrieved also after traditional and AI inpainting, permitting to unveil the semantic modification the image has undergone via image-text mismatch analysis.
Abstract (translated)
我们提出了一种用于文本嵌入的高负载图像水印方法，其中将对图像的语义描述——这可能也对应于输入的文本提示——嵌入到图像中。为了能够在大规模图像（如现代AI生成器产生的图像）中稳健地嵌入大量信息，所提出的方案建立在传统的水印技术基础上，该技术利用正交和Turbo码来提高鲁棒性，并结合频域嵌入和感知掩蔽技术以增强水印的不可见性。实验表明，所提出的方法对各种图像处理具有极强的稳健性，即使经过传统和AI的修复（inpainting）后，也能检索出嵌入的文本，这使得通过图像-文本不匹配分析揭示图像经历的语义修改成为可能。
URL
https://arxiv.org/abs/2509.24823
