首页> 外文会议>Soft Computing and Pattern Recognition, 2009. SOCPAR '09 >Damageless Digital Watermarking by Machine Learning: A Method of Key Generation for Information Extraction Using Artificial Neural Networks
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Damageless Digital Watermarking by Machine Learning: A Method of Key Generation for Information Extraction Using Artificial Neural Networks

机译:机器学习的无损数字水印:一种使用人工神经网络提取信息的密钥生成方法

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Soft computing in the area of information security is a promising field for the creation of intelligent solutions. This paper discusses a method for digital watermarking using artificial neural networks to realize secure copyright protection of visual information without any damage. The discussed watermark extraction keys and feature extraction keys identify the secure and unique hidden patterns for proper digital watermarks. In the experiments, we have shown that the proposed method is robust to high pass filtering and JPEG compression of visual information, only for those watermark extraction keys which were able to identify the proper hidden bit patterns from original visual information using corresponding feature extraction keys. The proposed method is to contribute to secure visual digital watermarking without damaging or losing any detailed data of visual information.
机译:信息安全领域的软计算是创建智能解决方案的一个有前途的领域。本文讨论了一种使用人工神经网络进行数字水印的方法,以实现对视觉信息的安全版权保护,而不会造成任何损害。讨论的水印提取键和特征提取键为正确的数字水印标识安全且独特的隐藏模式。在实验中,我们已经表明,该方法对视觉信息的高通滤波和JPEG压缩具有鲁棒性,仅适用于那些能够使用相应的特征提取键从原始视觉信息中识别适当的隐藏位模式的水印提取键。所提出的方法有助于在不破坏或丢失视觉信息的任何详细数据的情况下确保视觉数字水印的安全。

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