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Maximum Correlation Search Based Watermarking Scheme Resilient to RST

机译:基于基于水印方案的最大相关性搜索对RST的弹性方案

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Many of the watermarking schemes that claim resilience to geometrical distortions embed information into invariant or semi-invariant domains. However, the discretisation process required in such domains might lead to low correlation responses during watermarking detection. In this document, a new strategy is proposed to provide resilience to strong Rotation, Scaling and Translation (RST) distortions. The proposed detection process is based on a Genetic Algorithm (GA) that maximises the correlation coefficient between the originally embedded watermark and the input image. Comparisons between a previous scheme, based on Log-Polar Mapping (LPM), and the present approach are reported. Results show that even a simple insertion process provides more robustness, as well as a lower image degradation.
机译:许多水印方案,其要求将信息归因于几何扭曲,将信息嵌入到不变或半不变的域中。然而,在水印检测期间,这种域中所需的离散过程可能导致低相关响应。在本文档中,提出了一种新的策略,为强大的旋转,缩放和翻译(RST)扭曲提供弹性。所提出的检测过程基于遗传算法(GA),其最大化最初嵌入的水印和输入图像之间的相关系数。报告了先前方案之间的比较,基于日志极性映射(LPM)和本方法。结果表明,即使是简单的插入过程也提供了更强大的鲁棒性,以及较低的图像劣化。

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