Screen-shooting Resilient Watermarking Method for Document Image Based on Attention Mechanism

Screen-shooting resilient watermarking algorithms are of significant importance in fields such as copyright protection and traceability.Existing screen-shooting resilient watermarking algorithms mostly focus on natural images,neglecting research on document images.Document carriers inherently contain less redundant information,making it challenging to balance robustness and imperceptibility of the watermark.To address this issue,a screen-shooting resilient watermarking method for document image based on attention mechanism is proposed.To enhance the imperceptibility of the watermark,an attention feature fusion module is introduced in the encoder network to adaptively aggregate shallow and deep features.To improve the robustness of the algorithm for extraction,an adaptive channel-spatial attention module is designed in the decoder network to emphasize features that are particularly important in both channel and spatial dimensions.Additionally,a Moiré distortion layer is designed during screen-shoo-ting noise simulation to enhance the algorithm’s robustness against real Moiré distortions.Experimental results demonstrate that the proposed method achieves an average PSNR of 33.4 dB,SSIM of 0.988 5,RMSE of 5.48,and an average extraction accuracy of 99.49% in various screen-shooting scenarios.In terms of image quality and watermark robustness,the proposed method outperforms existing similar methods.