基于传统引导机制的深度鲁棒水印算法

郭学镜; 方毅翔; 赵怡; 张天助; 曾文超; 王俊祥

doi:10.11959/j.issn.2096-109x.2023031

您当前的位置：

首页 >

文章列表页 >

基于传统引导机制的深度鲁棒水印算法

学术论文 | 更新时间：2024-06-03

- 基于传统引导机制的深度鲁棒水印算法
- Traditional guidance mechanism based deep robust watermarking
- 网络与信息安全学报 2023年9卷第2期页码：175-183
- 作者机构：
- 作者简介：
  
  [ "郭学镜（1996- ），男，江西上饶人，景德镇陶瓷大学硕士生，主要研究方向为信息安全与数字图像处理" ]
  [ "方毅翔（1987- ），男，江西景德镇人，景德镇陶瓷大学讲师，主要研究方向为信息安全与数字图像处理" ]
  [ "赵怡（1985- ），女，江西南昌人，景德镇陶瓷大学实验师，主要研究方向为信息安全与数字图像处理" ]
  [ "张天助（1993- ），男，江西上饶人，景德镇陶瓷大学助理讲师，主要研究方向为信息安全与数字图像处理" ]
  [ "曾文超（1996- ），男，湖北宜昌人，景德镇陶瓷大学硕士生，主要研究方向为信息安全与数字图像处理" ]
  [ "王俊祥（1985- ），男，江西景德镇人，景德镇陶瓷大学教授，主要研究方向为信息安全与数字图像处理" ]
- 基金信息：
  
  国家自然科学基金;The National Natural Science Foundation of China(62062044);国家自然科学基金;The National Natural Science Foundation of China(62063010);江西省科技合作专项重点项目;The Science and Technology Cooperation Special Key Project of Jiangxi Province(20212BDH80021);景德镇市级科技计划项目;Jingdezhen Municipal Science and Technology Plan Project(2020ZDGG004)
- DOI：10.11959/j.issn.2096-109x.2023031
  中图分类号： TP393
- 网络首发：2023-04，
  
  纸质出版：2023-04-25
- 稿件说明：
移动端阅览
郭学镜, 方毅翔, 赵怡, 等. 基于传统引导机制的深度鲁棒水印算法[J]. 网络与信息安全学报, 2023,9(2):175-183.

Xuejing GUO, Yixiang FANG, Yi ZHAO, et al. Traditional guidance mechanism based deep robust watermarking[J]. Chinese Journal of Network and Information Security, 2023, 9(2): 175-183.
郭学镜, 方毅翔, 赵怡, 等. 基于传统引导机制的深度鲁棒水印算法[J]. 网络与信息安全学报, 2023,9(2):175-183. DOI： 10.11959/j.issn.2096-109x.2023031.

Xuejing GUO, Yixiang FANG, Yi ZHAO, et al. Traditional guidance mechanism based deep robust watermarking[J]. Chinese Journal of Network and Information Security, 2023, 9(2): 175-183. DOI： 10.11959/j.issn.2096-109x.2023031.

摘要

随着网络和多媒体技术的发展，多媒体数据逐渐成为人们获取信息的重要来源，数字媒体逐渐成为版权保护和防伪溯源主战场，版权保护新技术的重要性日益凸显，数字水印技术作为其中一种重要的版权保护手段得到重视。在信息传递过程中，含密数字媒体信息可能会受到噪声和外部干扰攻击，传统鲁棒数字水印技术正是围绕这些问题进行研究。然而，传统的鲁棒数字水印技术对不同类型攻击的综合抵抗能力有待提升。同时，由于其嵌入方式的局限性，传统的鲁棒数字水印算法对不同图像的泛化处理能力较弱。近年来，深度学习由于其强大的自学习能力被广泛应用于鲁棒数字水印技术研究。基于深度网络的鲁棒数字水印算法的初始化通常来源于随机的参数和特征，这会导致生成的模型质量不佳、训练时间过长，甚至无法收敛。结合两者的优点，采用传统的数字水印技术进行引导，兼顾深度网络的学习能力和传统鲁棒数字水印技术特征进行设计，提出一种基于传统引导机制的深度鲁棒数字水印算法。所提算法利用传统的鲁棒数字水印算法生成水印图像，设计的特征构造能够保证传统水印图像的鲁棒性。再利用U-Net结构将传统水印图像融合至深度网络，生成最终的含密图像。实验结果表明，所提算法能够提升含密图像抵抗各种攻击的鲁棒性，并且保证更好的视觉质量。

Abstract

With the development of network and multimedia technology

multimedia data has gradually become a key source of information for people

making digital media the primary battlefield for copyright protection and anti-counterfeit traceability.Digital watermarking techniques have been widely studied and recognized as important tools for copyright protection.However

the robustness of conventional digital watermarking methods is limited as sensitive digital media can easily be affected by noise and external interference during transmission.Then the existing powerful digital watermarking technology’s comprehensive resistance to all forms of attacks must be enhanced.Moreover

the conventional robust digital watermarking algorithm’s generalizability across a variety of image types is limited due to its embedding method.Deep learning has been widely used in the development of robust digital watermarking systems due to its self-learning abilities.However

current initialization techniques based on deep neural networks rely on random parameters and features

resulting in low-quality model generation

lengthy training times

and potential convergence issues.To address these challenges

a deep robust digital watermarking algorithm based on a traditional bootstrapping mechanism was proposed.It combined the benefits of both traditional digital watermarking techniques and deep neural networks

taking into account their learning abilities and robust characteristics.The algorithm used the classic robust digital watermarking algorithm to make watermarked photos

and the constructed feature guaranteed the resilience of traditional watermarked images.The final dense image was produced by fusing the conventionally watermarked image with the deep network using the U-Net structure.The testing results demonstrate that the technique can increase the stego image’s resistance to various attacks and provide superior visual quality compared to the conventional algorithm.

关键词

Keywords

references

BARNI M , BARTOLINI F , COX I J , et al . Digital watermarking for copyright protection:communications perspective [J ] . IEEE Communications Magazine , 2001 , 39 ( 8 ): 90 - 91 .

NIKOLAIDIS N , et al . Robust image watermarking in the spatial domain [J ] . Signal Processing , 1998 , 66 ( 3 ): 385 - 403 .

ZHANG W Y . Semi-fragile spatial watermarking based on local binary pattern operators [J ] . Optics Communications , 2011 , 284 ( 16/17 ): 3904 - 3912 .

COX I J , KILIAN J , LEIGHTON F T , et al . Secure spread spectrum watermarking for multimedia [J ] . IEEE Transactions on Image Processing , 1997 , 6 ( 12 ): 1673 - 1687 .

HSU C T , WU J L . Hidden digital watermarks in images [J ] . IEEE Transactions on Image Processing , 1999 , 8 ( 1 ): 58 - 68 .

HUANG J W , SHI Y Q , SHI Y . Embedding image watermarks in dc components [J ] . IEEE Transactions on Circuits and Systems for Video Technology , 2000 , 10 ( 6 ): 974 - 979 .

CHU W C . DCT-based image watermarking using subsampling [J ] . IEEE Transactions on Multimedia , 2003 , 5 ( 1 ): 34 - 38 .

AHMED N , NATARAJAN T , RAO K R . Discrete cosine transform [J ] . IEEE Transactions on Computers , 1974 , 23 ( 1 ): 90 - 93 .

BYUN S W , SON H S , LEE S P . Fast and robust watermarking method based on DCT specific location [J ] . IEEE Access , 2019 , 7 : 100706 - 100718 .

COX I , MILLER M , BLOOM J , et al . Digital watermarking and steganography [M ] . Morgan Kaufmann Publishers Inc , 2007 .

NEZHADARYA E , WANG Z J , WARD R K . Robust image watermarking based on multiscale gradient direction quantization [J ] . IEEE Transactions on Information Forensics and Security , 2011 , 6 ( 4 ): 1200 - 1213 .

CHANG C C . SVD-based digital image watermarking scheme [J ] . Pattern Recognition Letters , 2005 , 26 ( 10 ): 1577 - 1586 .

MOHAMMAD A A , ALHAT S S . An improved SVD-based watermarking scheme for protecting rightful ownership [J ] . Signal Processing , 2008 , 88 ( 9 ): 2158 - 2180 .

NI R R , RUAN Q Q , LIU J Q . Tampering estimation watermarking based on lifting wavelet and chaotic sequence [C ] // Proceedings of 2006 8th International Conference on Signal Processing . 2006 .

GU Q L , GAP T G . A novel reversible robust watermarking algorithm based on chaotic system [J ] . Digital Signal Processing , 2013 , 23 ( 1 ): 213 - 217 .

SEO J S , YOO C D . Image watermarking based on invariant regions of scale-space representation [J ] . IEEE Transactions on Signal Processing , 2006 , 54 ( 4 ): 1537 - 1549 .

LU C S , SUN S W , HSU C Y , et al . Media hash-dependent image watermarking resilient against both geometric attacks and estimation attacks based on false positive-oriented detection [J ] . IEEE Transactions on Multimedia , 2006 , 8 ( 4 ): 668 - 685 .

LIN C Y , WU M , BLOOM J A , et al . Rotation,scale,and translation resilient watermarking for images [J ] . IEEE Transactions on Image Processing:a Publication of the IEEE Signal Processing Society , 2001 , 10 ( 5 ): 767 - 782 .

ZHENG D , ZHAO J , EL SADDIK A . RST-invariant digital image watermarking based on log-polar mapping and phase correlation [J ] . IEEE Transactions on Circuits and Systems for Video Technology , 2003 , 13 ( 8 ): 753 - 765 .

KIM H S , LEE H K . Invariant image watermark using Zernike moments [J ] . IEEE Transactions on Circuits and Systems for Video Technology , 2003 , 13 ( 8 ): 766 - 775 .

XIN Y Q , LIAO S , PAWLAK M . A multibit geometrically robust image watermark based on Zernike moments [C ] // Proceedings of the 17th International Conference on Pattern Recognition . 2004 : 861 - 864 .

XIN Y , LIAO S , PAWLAK M . Geometrically robust image watermarking on a circular domain [J ] . Pattern Recognition , 2007 , 40 ( 1 ): 3740 - 3752 .

GOLABI S . Non-unit mapped radial moments platform for robust,geometric invariant image watermarking and reversible data hiding [J ] . Information Sciences , 2018 , 447 : 104 - 116 .

ZHU J , RUSSELL K , JUSTIN J , et al . Hidden:hiding data with deep networks [C ] // Proceedings of ECCV . 2018 : 682 - 697 .

GOODFELLOW I J , JEAN P A , MEHDI M , et al . Generative adversarial nets [C ] // Proceedings of the 27th International Conference on Neural Information Processing Systems . 2014 : 2672 - 2680 .

TANCIK M , MILDENHALL B , NG R . StegaStamp:invisible hyperlinks in physical photographs [C ] // Proceedings of 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . 2020 : 2114 - 2123 .

RONNEBERGER O , FISCHER P , BROX T . U-Net:convolutional networks for biomedical image segmentation [C ] // Proceedings of Medical Image Computing and Computer-Assisted Intervention-MICCAI 2015 . 2015 : 234 - 241 .

HUISKES M J , LEW M S . The MIR flickr retrieval evaluation [C ] // Proceedings of the 1st ACM International Conference on Multimedia Information Retrieval . 2008 : 39 - 43 .

浏览量

128

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

载体独立的抗屏摄信息膜叠加水印算法