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Image authentication algorithm with recovery capabilities based on neural networks in the DCT domain

机译:DCT域中基于神经网络的具有恢复能力的图像认证算法

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In this study, the authors propose an image authentication algorithm in the DCT domain based on neural networks. The watermark is constructed from the image to be watermarked. It consists of the average value of each 8 × 8 block of the image. Each average value of a block is inserted in another supporting block sufficiently distant from the protected block to prevent simultaneous deterioration of the image and the recovery data during local image tampering. Embedding is performed in the middle frequency coefficients of the DCT transform. In addition, a neural network is trained and used later to recover tampered regions of the image. Experimental results shows that the proposed method is robust to JPEG compression and can also not only localise alterations but also recover them.
机译:在这项研究中,作者提出了基于神经网络的DCT域中的图像认证算法。水印由要加水印的图像构成。它由图像的每个8×8块的平均值组成。块的每个平均值插入到距离受保护块足够远的另一个支持块中,以防止在局部图像篡改期间图像和恢复数据同时劣化。嵌入是在DCT变换的中频系数中执行的。此外,神经网络经过训练后可用于恢复图像的篡改区域。实验结果表明,该方法对JPEG压缩具有鲁棒性,不仅可以定位变化,而且可以恢复变化。

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