A Deep Learning-based Audio-in-Image Watermarking Scheme
A Deep Learning-based Audio-in-Image Watermarking Scheme
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DOI：
10.1109/vcip53242.2021.9675375
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发表时间：
2021-10
期刊：
影响因子：
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通讯作者：
A. Das;Xin Zhong
中科院分区：
文献类型：
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作者：
A. Das;Xin Zhong
提出了一种基于深度学习的图像中音频水印方案。图像中音频水印是在封面图像上隐蔽地嵌入和提取音频水印的过程。使用音频水印可以为不同的下游应用打开可能性。为了实现适应日益多样化需求的图像中音频水印，设计了一种神经网络架构，以无监督的方式自动学习水印过程。此外，本文还建立了一个相似度网络来识别失真情况下的音频水印，从而提高了方法的鲁棒性。实验结果表明，所提出的盲音频图像水印方案具有较高的保真度和鲁棒性。
This paper presents a deep learning-based audio-in-image watermarking scheme. Audio-in-image watermarking is the process of covertly embedding and extracting audio watermarks on a cover-image. Using audio watermarks can open up possibilities for different downstream applications. For the purpose of implementing an audio-in-image watermarking that adapts to the demands of increasingly diverse situations, a neural network architecture is designed to automatically learn the watermarking process in an unsupervised manner. In addition, a similarity network is developed to recognize the audio watermarks under distortions, therefore providing robustness to the proposed method. Experimental results have shown high fidelity and robustness of the proposed blind audio-in-image watermarking scheme.