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Image steganography based on pixel ranking and Particle Swarm Optimization

机译:基于像素排序和粒子群优化的图像隐写术

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摘要

We propose a novel approach for image steganog-raphy by taking the advantages of Particle Swarm Optimization (PSO) and Least Significant Bits (LSBs) replacement. This technique is based on hiding the Most Significant Bits (MSBs) of secret image pixels in LSBs of a host image. The proposed method finds the best pixel in order to embed. We define four feature functions and four corresponding coefficients to rank the pixels. The features and the coefficients are defined based on the MSBs of host image. Our method defines a special secret key for each host image based on PSO in which, each particle represents a potential solution and we can evaluate all of them. This novelty causes better exploration of search space in order to find suitable pixel ranking and higher security. The experimental results show the superiority of this approach over the state-of-the-art methods.
机译:我们利用粒子群优化(PSO)和最低有效位(LSB)替换的优点,提出了一种针对图像隐写的新方法。此技术基于在主机图像的LSB中隐藏秘密图像像素的最高有效位(MSB)。所提出的方法找到最佳像素以便嵌入。我们定义了四个特征函数和四个相应的系数来对像素进行排名。特征和系数是基于宿主图像的MSB定义的。我们的方法基于PSO为每个主机图像定义一个特殊的秘密密钥,其中每个粒子代表一个潜在的解决方案,我们可以对所有这些密钥进行评估。这种新颖性可以更好地探索搜索空间,以找到合适的像素等级和更高的安全性。实验结果表明,该方法优于最新方法。

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