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Watermarking-based image authentication with recovery capability using halftoning technique

机译:使用半色调技术的具有恢复能力的基于水印的图像认证

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In this paper two watermarking algorithms for image content authentication with localization and recovery capability of the tampered regions are proposed. In both algorithms, a halftone version of the original gray-scale image is used as an approximated version of the host image (image digest) which is then embedded as a watermark sequence into given transform domains of the host image. In the first algorithm, the Integer Wavelet Transform (IWT) is used for watermark embedding which is denominated WIA-IWT (Watermarking-based Image Authentication using IWT), while in the second one, the Discrete Cosine Transform (DCT) domain is used for this purpose, we call this algorithm WIA-DCT (Watermarking-based Image Authentication using DCT). In the authentication stage the tampered regions are detected using the Structural Similarity index (SSIM) criterion, which are then recovered using the extracted halftone image. In the recovery stage, a Multilayer Perceptron (MLP) neural network is used to carry out an inverse halftoning process to improve the recovered image quality. The experimental results demonstrate the robustness of both algorithms against content preserved modifications, such as JPEG compression, as well as an effective authentication and recovery capability. Also the proposed algorithms are compared with some previously proposed content authentication algorithms with recovery capability to show the better performance of the proposed algorithms.
机译:提出了两种具有篡改区域定位和恢复能力的图像内容认证水印算法。在这两种算法中,原始灰度图像的半色调版本都用作宿主图像(图像摘要)的近似版本,然后将其作为水印序列嵌入到宿主图像的给定变换域中。在第一种算法中,整数小波变换(IWT)用于水印嵌入,称为WIA-IWT(使用IWT的基于水印的图像认证),而在第二种算法中,离散余弦变换(DCT)域用于为此,我们将此算法称为WIA-DCT(使用DCT的基于水印的图像认证)。在认证阶段,使用结构相似性索引(SSIM)标准检测篡改区域,然后使用提取的半色调图像将其恢复。在恢复阶段,使用多层感知器(MLP)神经网络进行逆半色调处理,以提高恢复的图像质量。实验结果证明了这两种算法针对内容保留的修改(如JPEG压缩)的鲁棒性以及有效的身份验证和恢复功能。还将所提出的算法与一些先前提出的具有恢复能力的内容认证算法进行比较,以显示所提出算法的更好性能。

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