基于PCNN与粗集理论的细胞图像二重数字水印算法  

Double digital watermarking algorithm for cell images based on PCNN and rough set theory

作　　者：林冬梅[1,2] 马义德[2] 张北斗[2] 

机构地区：[1]兰州理工大学电气工程与信息工程学院,兰州730050 [2]兰州大学信息科学与工程学院,兰州730000

出　　处：《计算机应用研究》2010年第2期721-725,共5页Application Research of Computers

基　　金：国家自然科学基金资助项目(60872109);国家教育部新世纪优秀人才支持计划项目(NCET-06-0900);兰州大学交叉学科青年创新研究基金资助项目(LZUJC2007013)

摘　　要：结合脉冲耦合神经网络与粗集理论,提出了一种空频域结合的二重水印算法,用于生物细胞图像的版权保护。首先在小波变换域中用粗集理论的方法找出水印嵌入位置,嵌入第一重水印信息,在此基础上,找出图像空间域中纹理复杂区域再次嵌入水印;然后讨论了水印的提取方法;最后进行了鲁棒性检测。仿真表明,该算法具有较强的不可见性和较好的鲁棒性,能准确地提取出水印信息,可以有效地对生物细胞图像进行版权保护。Combining pulse coupled neural network （ PCNN ） and rough set theory can get good achievements in digital image processing because of PCNN＇ s biology background and rough set theory＇ s excellent ability to categorize difference things. After giving the analysis of the need for biological cell images to be copyright protected, presented a new spatial-frequency-domain-based double watermarking algorithm. Firstly, used the method of rough set theory to find the location suitable for watermarking in the wavelet transform domain, and embedded the first watermarking. Then, found the regions full of textures in the spatial domain of the image with the first watermarking embedded, to embed the second watermarking. Secondly, gave a brief discussion on the watermarking extraction. Finally, also presented the robustness detection. Experimental results indicate that the algorithm has good invisibility and strong robustness. It is a feasible and effective digital image watermarking algorithm.

关 键 词：脉冲耦合神经网络 粗集理论 多重数字水印 小波变换 鲁棒性 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]