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Color-Identification System Using the Sandglass-Type Neural Networks

机译:使用沙漏型神经网络的颜色识别系统

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摘要

A problem for the illegal copy of the digital image, which overflows on WWW, and the copyright protection of the image information becomes serious. Electronic watermark technology is being watched as that strong countermeasure. However, there is a problem that the problem that quality of output deteriorates, and the codes put inside are analyzed. In this paper, a neuro-color compression ID system with no quality of output deterioration, which sets up security for the image, is proposed. The position information of pixel chosen at random from the color image and RGB value are compressed with a proposal system by using sandglass type neural network (SNN). The information that it is compressed and the combination weight of SNN are called neuro-color compression ID. Moreover, neuro-color compression ID can be restored by using the position information of the number of pixel of SNN chosen at random. It is possible that the possible system of the prevention of an illegal copy and the copyright protection is built by making either of the position information of neuro-color compression ID, the number of pixel that it is chosen, or pixels base an image license. Furthermore, because it doesn't need to put a code inside like an electronic watermark, even the field that a demand for the information secret is severe can be used as a new watermark technology with no quality of output deterioration. Furthermore, in order to show the effectiveness of the proposed method, simulations are done. This proposed method was recognized as the patent.
机译:数字图像的非法复制会在WWW上泛滥,并且图像信息的版权保护变得很严重。电子水印技术被视为一种强有力的对策。然而,存在这样的问题,即输出质量劣化的问题,并且分析了放入内部的代码。本文提出了一种不降低输出质量的神经彩色压缩ID系统,该系统为图像设置了安全性。通过使用沙漏型神经网络(SNN)的提案系统压缩从彩色图像和RGB值中随机选择的像素的位置信息。它被压缩的信息和SNN的组合权重称为神经颜色压缩ID。此外,可以通过使用随机选择的SNN的像素数的位置信息来恢复神经颜色压缩ID。可以通过使神经色压缩ID的位置信息,所选择的像素数或基于图像许可证的像素中的任意一个来构建防止非法复制和版权保护的可能系统。此外,由于不需要像电子水印一样在内部放入代码,因此即使对信息秘密的要求很高的领域也可以用作新的水印技术,而不会降低输出质量。此外,为了显示该方法的有效性,进行了仿真。该提议的方法被认为是专利。

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