基于神经网络的数字水印技术

Yu Chang-hui, Feng Wan-li, Z. Hong
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引用次数: 6

摘要

为了在不可见的前提下增强数字水印的鲁棒性,本文从三个不同的处理阶段对数字水印技术进行了研究。(1)第一阶段是水印信号预处理。将二值灰度图像生成的水印信号先由混沌函数进行高度非线性处理,再由神经网络进行高度非线性处理,大大提高了水印的保密性;(2)第二阶段是水印嵌入强度程度。首先构造并训练神经网络。将训练好的神经网络用于水印的嵌入和提取,实现水印算法的盲检测;(3)第三阶段是水印的嵌入和提取。通过训练好的神经网络将处理后的水印信号嵌入到原始图像的空域中。并利用神经网络对水印进行提取和检测。实验结果表明,该算法具有良好的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The digital watermarking technology based on neural networks
This paper concerns the digital watermarking technology on three different processing stages in order to enhance the robustness of digital watermarking under the premise of invisibility. (1)The first stage is watermark signal pre-processing. The watermark signal created using binary gray images is taken the highly nonlinear processing by the chaotic function first and then by the neural network, which enhances the degree of watermark confidentiality greatly; (2)The second stage is watermark embedding strength degree. First a neural network is constructed and trained. The trained neural network can be used in watermark embedding and extraction by which a watermark algorithm can be achieved to do blind detection; (3)The third stage is watermark embedding and extraction. The treated watermark signal is embedded into the airspace of the original image through the trained neural network. And the neural network is also used to extract and detect the watermark. Proved by experimental results, this algorithm has good robustness.
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