共查询到19条相似文献,搜索用时 93 毫秒
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基于二维元胞自动机和Logistic混沌映射,提出了一种新的图像加密算法.该算法主要思想是采用Logistic映射设计一种非线性耦合结构来对明文像素矩阵进行置乱,然后在分析元胞自动机的混沌和密码学性质的基础上构造一个二维伪随机数矩阵来进行图像加密.仿真实验结果表明,该算法具有较大的密钥空间,对密钥具有极高的敏感性,密文具有良好的扩散和统计特性,可以有效地抵御穷举攻击、敏感性攻击以及统计攻击等. 相似文献
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为了使加密系统拥有图像认证功能,能够防止图像在存储与传输过程中被各种攻击肆意篡改,并提高其加解密速度以及安全性,使可逆线性元胞自动机具备记忆贮存功能,提出一种可逆线性记忆元胞自动机。采用混沌映射与可逆线性记忆元胞自动机相融合的图像认证加密算法来增强加密系统的性能,采用的是图像块加密算法,而非传统的密码流。首先采用二维分段线性混沌映射对初始明文图像进行置乱,改变像素位置;然后对置乱图像进行分块,并利用Logistic映射和可逆线性记忆元胞自动机对每一块进行扩散加密处理,改变其像素值,随后将这些加密后的分块密文组合起来形成密文图像;将HASH方程引入到本文算法中,使其拥有图像认证功能。借助MATLAB仿真软件来验证本文算法,结果表明:所提出的图像认证加密新算法具有优异的加密性能,扩散机制高度安全,计算效率高,其密钥空间足够大,抗攻击能力大幅度提升。 相似文献
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提出了一种结合提升小波和QR码的盲水印实现。嵌入水印时,首先对需要版权保护的图像进行提升小波变换,然后对水印图像进行QR码编码处理,再对得到的QR码图像进行混沌处理以提高算法的安全性,最后将经过QR码编码、混沌处理的水印信息通过元胞自动机处理嵌入到原始图像的提升小波逼近子图中。水印提取时,对经过上述处理后的图像应用元胞自动机、混沌系统、QR码解码得到原始水印信息。仿真结果表明,该实现方法具有较高的鲁棒性,能够抵抗剪切、修改、噪声等攻击。该实现方法能够广泛应用于版权保护领域,具有一定的实用价值。 相似文献
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提出了基于耦合混沌和触发细胞自动机的图像加密算法。首先用耦合混沌系统对图像进行加密,然后用耦合二维细胞自动机再次加密,最后用混沌序列对图像进行置乱。加密过程中同时运用了分组加密和流加密方法。仿真实验结果表明,该加密算法实现简单,扩散和混淆效果比较理想,有较强的抗攻击能力,具有良好的加密效果。 相似文献
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一维触发元胞自动机加密系统的缺点是密钥空间小[1],二维触发元胞自动机在几乎不增加计算量及复杂度的同时,极大地扩张了密钥空间。简述二维触发元胞自动机的基本理论,应用其触发规则建立动态密码系统,完成加密解密,并根据程序的最终测试数据,进行性能分析。 相似文献
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Yao Qin Mengyang Feng Huchuan Lu Garrison W. Cottrell 《International Journal of Computer Vision》2018,126(7):751-770
Saliency detection, finding the most important parts of an image, has become increasingly popular in computer vision. In this paper, we introduce Hierarchical Cellular Automata (HCA)—a temporally evolving model to intelligently detect salient objects. HCA consists of two main components: Single-layer Cellular Automata (SCA) and Cuboid Cellular Automata (CCA). As an unsupervised propagation mechanism, Single-layer Cellular Automata can exploit the intrinsic relevance of similar regions through interactions with neighbors. Low-level image features as well as high-level semantic information extracted from deep neural networks are incorporated into the SCA to measure the correlation between different image patches. With these hierarchical deep features, an impact factor matrix and a coherence matrix are constructed to balance the influences on each cell’s next state. The saliency values of all cells are iteratively updated according to a well-defined update rule. Furthermore, we propose CCA to integrate multiple saliency maps generated by SCA at different scales in a Bayesian framework. Therefore, single-layer propagation and multi-scale integration are jointly modeled in our unified HCA. Surprisingly, we find that the SCA can improve all existing methods that we applied it to, resulting in a similar precision level regardless of the original results. The CCA can act as an efficient pixel-wise aggregation algorithm that can integrate state-of-the-art methods, resulting in even better results. Extensive experiments on four challenging datasets demonstrate that the proposed algorithm outperforms state-of-the-art conventional methods and is competitive with deep learning based approaches. 相似文献
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《Advances in Engineering Software》1999,30(6):419-437
The following problem is solved: Given a Cellular Automaton with continuous state space which simulates a physical system or process, use a Genetic Algorithm in order to find a Cellular Automaton with discrete state space, having the smallest possible lattice size and the smallest possible number of discrete states, the results of which are as close as possible to the results of the Cellular Automaton with continuous state space. The Cellular Automaton with discrete state space evolves much faster than the Cellular Automaton with continuous state space. The state spaces of two Cellular Automata have been discretized using a Genetic Algorithm. The first Cellular Automaton simulates the two-dimensional photoresist etching process in integrated circuit fabrication and the second is used to predict forest fire spreading. A general method for the discretization of the state space of Cellular Automata using a Genetic Algorithm is also presented. The aim of this work is to provide a method for accelerating the execution of algorithms based on Cellular Automata (Cellular Automata algorithms) and to build a bridge between Cellular Automata as models for physical systems and processes and Cellular Automata as a VLSI architecture. 相似文献
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Olu Lafe 《Engineering Applications of Artificial Intelligence》1997,10(6):581-591
A family of basis functions, generated from the evolving states of Cellular Automata (CA), is used to compress and encrypt data. The operations required in encoding and decoding the data are described under the umbrella Cellular Automata Transforms (CAT). There is a huge number of these transform bases. CAT can be used in the way other mathematical transforms (e.g., Fourier, Discrete Cosine, Laplace, Wavelet, etc.) are utilized. In data-compression applications, the rules and pertinent keys used to generate the CA are selected to favor those that yield basis functions with the best information-packing characteristics. On the other hand, for encryption the selection is biased towards those with the tendency to yield an avalanche effect. In the latter case the transform process must be error-free. 相似文献
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细胞神经网络图像恢复新方法的研究 总被引:1,自引:0,他引:1
结合二维细胞自动机(CA)和细胞神经网络通用二进制神经元(CNN-UBN)设计了两种新的用于噪声图像恢复的细胞神经网络(CNN)。这两种网络的联合处理图像结果明显优于长度为3和5的普通中值滤波恢复方法,且具有速度快、结构简单、易于硬件集成等优点,是一种新颖实用的图像恢复算法。 相似文献
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不同于传统的去相关,去冗余的压缩方法,提出一种基于元胞自动机模型的二值图像压缩算法。该算法用遗传规划算法搜索出较优的元胞自动机规则后,对分块后的二值图像矢量进行元胞自动机变换,利用元胞自动机的变换状态多样性等特点,生成相邻矢量,将变换次数作为码本。实验表明:该算法经过4次以内的元胞自动机变换即可生成较优的相邻矢量,具有编码时间短、重建图像的质量好、压缩率高、适应性强等特点,并且与其它压缩算法结合性好。 相似文献
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演化元胞自动机函数优化算法案例研究 总被引:7,自引:1,他引:6
BUMP是一个超多维,超多峰,超非线性的问题,被广泛应用于各种演化算法的性能比较。但最好解是未知的。基于元胞自动机的遗传算法报告了BUMP曾经发表过的最好解。该文设计了基于演化元胞自动机的新算法(ECAA)并获得了更好的结果。文中详细讨论了算法中各算子的设计方法及其在算法中扮演的角色,分析了该算法的极度并行,天然局部搜索等重要特性。 相似文献