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A Graph Theory Practice on Transformed Image: A Random Image Steganography

机译:转换图像的图论实践:随机图像隐写术

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摘要

Modern day information age is enriched with the advanced network communication expertise but unfortunately at the same time encounters infinite security issues when dealing with secret and/or private information. The storage and transmission of the secret information become highly essential and have led to a deluge of research in this field. In this paper, an optimistic effort has been taken to combine graceful graph along with integer wavelet transform (IWT) to implement random image steganography for secure communication. The implementation part begins with the conversion of cover image into wavelet coefficients through IWT and is followed by embedding secret image in the randomly selected coefficients through graph theory. Finally stegoimage is obtained by applying inverse IWT. This method provides a maximum of 44 dB peak signal to noise ratio (PSNR) for 266646 bits. Thus, the proposed method gives high imperceptibility through high PSNR value and high embedding capacity in the cover image due to adaptive embedding scheme and high robustness against blind attack through graph theoretic random selection of coefficients.
机译:现代信息时代丰富了先进的网络通信专业知识,但不幸的是,同时在处理秘密和/或私人信息时遇到无限的安全问题。秘密信息的存储和传输变得非常重要,并导致了在这一领域的研究卓越。在本文中,已经采取了乐观的努力来将优雅的图表与整数小波变换(IWT)相结合,以实现随机图像隐写进行安全通信。实施部分以IWT转换为小波系数的覆盖图像转换,然后通过图形理论将秘密图像嵌入到随机选择的系数中。最后通过施加逆IWT获得SegoImage。该方法为266646位提供最多44dB峰值信号(PSNR)。因此,由于自适应嵌入方案和通过图形无规的系数的图形无随机选择,通过覆盖图像中的高PSNR值和封面图像中的高嵌入容量,通过高psnr值和高嵌入容量提供高难以察觉。

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