A Novel Deep Learning Architecture for Image Hiding

S. Rathnam, G. Rao
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引用次数: 5

Abstract

Watermarking is a today's digital hiding technique within certain electronic content: for example, message, image, video, or audio recordings. Recent times, it was created as a modern copyright security tool. The pattern in zero watermarking technique isn't really inserted directly in the cover image, but has a logical relation with that cover image. In this article, we propose a powerful convolution neural Networks (CNN) and deep learning algorithm-based-watermarking technique in which the CNN produces robust inherent selected features and is merged with the XOR activity of host's watermark sequence. The outcomes of our proposed method present the courage of the watermark counter to many typical image processing techniques.
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一种新的图像隐藏深度学习架构
水印是当今在某些电子内容(例如消息、图像、视频或音频记录)中使用的一种数字隐藏技术。最近,它被创建为一个现代版权安全工具。零水印技术中的模式并不是直接插入到封面图像中,而是与封面图像有一种逻辑关系。在本文中,我们提出了一种基于卷积神经网络(CNN)和深度学习算法的强大水印技术,其中CNN产生鲁棒的固有选择特征,并与宿主水印序列的异或活动合并。该方法的结果表明,水印计数器与许多典型的图像处理技术相比具有一定的优越性。
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