吉林大学学报(工学版) ›› 2017, Vol. 47 ›› Issue (1): 249-254.doi: 10.13229/j.cnki.jdxbgxb201701036

• 论文 • 上一篇    下一篇

高 鲁 棒 性 的 图 像 水 印 算 法

赵博, 秦贵和   

  1. 吉林大学 计算机科学与技术学院, 长春 130012
  • 收稿日期:2015-10-15 出版日期:2017-01-20 发布日期:2017-01-20
  • 通讯作者: 秦贵和(1962-),男,教授,博士生导师.研究方向:嵌入式与智能控制.E-mail:qingh@jlu.edu.cn
  • 作者简介:赵博(1988-),男,博士研究生.研究方向:图像处理.E-mail:wolfers509@126.com
  • 基金资助:
    吉林省科技发展计划项目(20150204034GX).

High robustness image watermarking algorithm

ZHAO Bo, QIN Gui-he   

  1. College of Computer Science and Technology, Jilin University, Changchun 130012,China
  • Received:2015-10-15 Online:2017-01-20 Published:2017-01-20

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摘要： 首先提取原图像基于视觉注意模型的显著图,然后通过NMF分解得到降维显著图作为灰度水印图像,之后通过混沌加密算法对水印图像进行置乱,将置乱后的水印信息通过DCT-SVD变换嵌入原图像的低频分量中。在接收端,对接收到的图像进行水印提取和解密操作得到原始灰度水印图像,即原图像的显著图,同时提取接收图像的显著图,通过对比原图像显著图与接收图像显著图的差异性,利用基于Lorenz曲线的差异算法与合理阈值判断接收图像是否受到噪声干扰或人为篡改。与其他类似算法的对比结果表明, 该算法针对噪声干扰与人为篡改有着很好的区分性。

关键词: 计算机应用, 视觉注意模型, 图像水印, Lorenz曲线, 图像认证

Abstract: First, the saliency is extracted from the original image based on visual attention model. Then, the image is decomposed by Non-negative Matrix Factorization (NMF) to reduce the dimension and scrambled by chaotic encryption. The decomposed saliency map is embedded into the frequency component of the original image by DCT-SVD transform. At the receiving terminal, the watermarking is extracted from the received image, and the saliency map of the received image is also extracted. Finally, comparison of the difference between the received image's saliency map and watermarking, the Lorenz curve and the reasonable threshold are used to determine whether the received image is changed by noise or artificial tampering. Compared with other similar algorithms, the proposed algorithm has good discrimination against noise interference and artificial tampering.

Key words: computer application, visual attention model, image watermarking, Lorenz curve, image authentication

中图分类号: 

  • TP751.1
[1] Lu C S, Liao H Y M. Multipurpose watermarking for image authentication and protection[J]. IEEE Transactions on Image Processing, 2001, 10(10): 1579-1592.
[2] Maeno K,Sun Q,Chang S F,et al.New semi-fragile image authentication watermarking techniques using random bias and nonuniform quantization[J].IEEE Transactions on Multimedia,2006,8(1):32-45.
[3] Lin C Y, Chang S F. A robust image authentication method distinguishing JPEG compression from malicious manipulation[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2001, 11(2): 153-168.
[4] Ho C K, Li C T. Semi-fragile watermarking scheme for authentication of JPEG images[J].International Conference on Information Technology: Coding and Computing,2004,1(6): 7-11.
[5] Ko C. A novel semi-fragile watermarking technique for image authentication[C]∥Proceedings of the Sixth IASTED International Conferenceon on (Signal and Image Processing),Marina Del Rey,2004.
[6] Loukhaoukha K, Nabti M, Zebbiche K. A robust SVD-based image watermarking using a multi-objective particle swarm optimization[J]. Opto Electronics Review, 2014, 22(1):45-54.
[7] Piva A, Bartolini F, Caldelli R. Self recovery authentication of images in the DWT domain[J]. International Journal of Image and Graphics, 2005, 5(01): 149-165.
[8] 朱光, 师文, 朱学芳,等. 结合SURF特征的多功能彩色图像水印算法[J]. 中国图象图形学报, 2013, 18(12): 1694-1702.
Zhu Guang,Shi Wen,Zhu Xue-fang,et al. Multi-purpose watermark algorithm of color images based on SURF[J]. Journal of Image and Graphics,2013,18(12):1694-1702.
[9] 王友卫, 刘元宁, 朱晓冬. 用于图像内容认证的半脆弱水印新算法[J]. 浙江大学学报:工学版, 2013, 6(6):969-976.
Wang You-wei,Liu Yuan-ning,Zhu Xiao-dong. Novel semi-fragile watermarking algorithm for image content authentication[J]. Journal of Zhejiang University(Engineering Science), 2013, 6(6):969-976.
[10] Preda R O. Semi-fragile watermarking for image authentication with sensitive tamper localization in the wavelet domain[J]. Measurement, 2013, 46(1): 367-373.
[11] Michison G. The organization of sequential memory: sparse representation and the targeting problem[R]. In:Seelen W V,Shaw G.1einbos U M.Organization of Neural Networks. VCH Verlagsgesellsehaft, Weinheim,1988:347-367.
[12] 赵宏伟, 陈霄, 刘萍萍,等. 视觉显著目标的自适应分割[J]. 光学精密工程, 2013,21(2):531-538.
Zhao Hong-wei,Chen Xiao,Liu Ping-ping et al.Adaptive segmentation for visual salient object[J].Optics and Precision Engineering,2013,21(2):531-538.
[13] Monga V, Mihcak K M. Robust and secure image hashing via non-negative matrix Factorizations[J]. IEEE Trans on Information Forensics and Security,2007,2(3):376-390.
[14] 易开祥, 孙鑫, 石教英. 一种基于混沌序列的图像加密算法[J]. 计算机辅助设计与图形学学报,2000,12:672-676.
Yi Kai-xiang, Sun Xin,Shi Jiao-ying. An image encryption arithmetic based on chaotic sequences[J]. Journal of Computer Aided Design and Computer Graphics,2000,12:672-676.
[15] 刘瑞祯, 谭铁牛. 基于奇异值分解的数字图像水印方法[J]. 电子学报, 2001, 29(2):168-171.
Liu Rui-zhen, Tan Tie-niu. SVD based digital watermarking method[J]. Acta Electronica Sinica, 2001, 29(2): 168-171.
[16] Amit K S, Mayank D, Anand M. Hybrid technique for robust and imperceptible image watermarking in DWT-DCT-SVD domain[J]. National Academy Science Letters 2014, 37(4): 351-358.
[17] Singh A, Tayal A, Choice of wavelet from wavelet families for DWT-DCT-SVD image watermarking[J]. International Journal of Computer Applications,2012, 48(17):9-14.
[18] Qi X, Xin X. A singular-value-based semi-fragile watermarking scheme for image content authentication with tamper localization[J]. Journal of Visual Communication & Image Representation, 2015, 30: 312-327.
[19] Qi X, Xin X. A quantization-based semi-fragile watermarking scheme for image content authentication[J]. Journal of Visual Communication & Image Representation, 2011, 22(2):187-200.
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