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A steganography embedding method based on edge identification and XOR coding

机译:基于边缘识别和异或编码的隐写法嵌入方法

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In this paper, we present a novel image steganography algorithm that combines the strengths of edge detection and XOR coding, to conceal a secret message either in the spatial domain or an Integer Wavelet Transform (IWT) based transform domain of the cover image. Edge detection enables the identification of sharp edges in the cover image that when embedding in would cause less degradation to the image quality compared to embedding in a pre-specified set of pixels that do not differentiate between sharp and smooth areas. This is motivated by the fact that the human visual system (HVS) is less sensitive to changes in sharp contrast areas compared to uniform areas of the image. The edge detection method presented here is capable of estimating the exact edge intensities for both the cover and stego images (before and after embedding the message), which is essential when extracting the message. The XOR coding, on the other hand, is a simple, yet effective, process that helps in reducing differences between the cover and stego images. In order to embed three secret message bits, the algorithm requires four bits of the cover image, but due to the coding mechanism, no more than two of the four bits will be changed when producing the stego image. The proposed method utilizes the sharpest regions of the image first and then gradually moves to the less sharp regions. Experimental results demonstrate that the proposed method has achieved better imperceptibility results than other popular steganography methods. Furthermore, when applying a textural feature steganalytic algorithm to differentiate between cover and stego images produced using various embedding rates, the proposed method maintained a good level of security compared to other steganography methods. (C) 2015 Elsevier Ltd. All rights reserved.
机译:在本文中,我们提出了一种新颖的图像隐写算法,该算法结合了边缘检测和XOR编码的优势,可以在覆盖图像的空间域或基于整数小波变换(IWT)的变换域中隐藏秘密消息。边缘检测可以识别封面图像中的锐利边缘,与嵌入在不区分锐利区域和平滑区域的预定像素集合中相比,嵌入时会导致图像质量的降低。这是因为与图像的均匀区域相比,人类视觉系统(HVS)对鲜明对比区域的变化不那么敏感。此处介绍的边缘检测方法能够估算出封面和隐密图像的准确边缘强度(在嵌入消息之前和之后),这在提取消息时必不可少。另一方面,XOR编码是一种简单但有效的过程,有助于减少封面图像与隐蔽图像之间的差异。为了嵌入三个秘密消息位,该算法需要覆盖图像的四个位,但是由于编码机制的原因,在生成隐身图像时,将不更改四个位中的两个位。所提出的方法首先利用图像的最锐利区域,然后逐渐移动到较不锐利区域。实验结果表明,与其他流行的隐写术相比,该方法具有更好的隐身性。此外,当应用纹理特征隐写分析算法来区分使用各种嵌入率生成的掩盖图像和隐身图像时,与其他隐写方法相比,该方法保持了良好的安全性。 (C)2015 Elsevier Ltd.保留所有权利。

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