Blind Image Watermarking Using a Sample Projection Approach

被引:42
|
作者
Akhaee, Mohammad Ali [1 ]
Sahraeian, Sayed Mohammad Ebrahim [2 ]
Jin, Craig [1 ]
机构
[1] Univ Sydney, Comp & Audio Res Lab CARLAB, Dept Elect & Informat Engn, Sydney, NSW 2006, Australia
[2] Texas A&M Univ, Genom Signal Proc GSP Lab, Dept Elect & Comp Engn, College Stn, TX 77843 USA
关键词
Gain attack; image watermarking; maximum likelihood detector; sample projection; SPREAD-SPECTRUM WATERMARKING; OPTIMUM DETECTION; DIGITAL IMAGE; ROBUST; INVARIANT; MODULATION;
D O I
10.1109/TIFS.2011.2146250
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
This paper presents a robust image watermarking scheme based on a sample projection approach. While we consider the human visual system in our watermarking algorithm, we use the low-frequency components of image blocks for data hiding to obtain high robustness against attacks. We use four samples of the approximation coefficients of the image blocks to construct a line segment in the 2-D space. The slope of this line segment, which is invariant to the gain factor, is employed for watermarking purpose. We embed the watermarking code by projecting the line segment on some specific lines according to message bits. To design a maximum likelihood decoder, we compute the distribution of the slope of the embedding line segment for Gaussian samples. The performance of the proposed technique is analytically investigated and verified via several simulations. Experimental results confirm the validity of our model and its high robustness against common attacks in comparison with similar watermarking techniques that are invariant to the gain attack.
引用
收藏
页码:883 / 893
页数:11
相关论文
共 50 条
  • [1] An improved sample projection approach for image watermarking
    Wang, Yuan-Gen
    Zhu, Guopu
    Huang, Jiwu
    DIGITAL SIGNAL PROCESSING, 2014, 24 : 135 - 143
  • [2] Blind gain invariant image watermarking using random projection approach
    Sadeghi, Mohammadreza
    Toosi, Ramin
    Akhaee, Mohammad Ali
    SIGNAL PROCESSING, 2019, 163 : 213 - 224
  • [3] Statistical learning based blind image watermarking approach
    Peng, Fanchen
    Wang, Xiangyang
    Li, Yang
    Niu, Panpan
    KNOWLEDGE-BASED SYSTEMS, 2024, 297
  • [4] A novel blind watermarking approach for medical image authentication using MinEigen value features
    Abdallah Soualmi
    Adel Alti
    Lamri Laouamer
    Multimedia Tools and Applications, 2021, 80 : 2279 - 2293
  • [5] A novel blind watermarking approach for medical image authentication using MinEigen value features
    Soualmi, Abdallah
    Alti, Adel
    Laouamer, Lamri
    MULTIMEDIA TOOLS AND APPLICATIONS, 2021, 80 (02) : 2279 - 2293
  • [6] A blind image watermarking using for copyright protection and tracing
    Li, HF
    Wang, SX
    Song, WW
    Wen, Q
    INTELLIGENCE AND SECURITY INFORMATICS, PROCEEDINGS, 2005, 3495 : 627 - 628
  • [7] A blind image watermarking using multiresolution visibility map
    M. Luong
    Q. B. Do
    A. Beghdadi
    Journal of Global Optimization, 2011, 49 : 435 - 448
  • [8] A blind image watermarking using multiresolution visibility map
    Luong, M.
    Do, Q. B.
    Beghdadi, A.
    JOURNAL OF GLOBAL OPTIMIZATION, 2011, 49 (03) : 435 - 448
  • [9] Adaptive Blind Watermarking Using Psychovisual Image Features
    PariZanganeh, Arezoo
    Ghorbanzadeh, Ghazaleh
    ShahreBabak, Zahra Nabizadeh
    Karimi, Nader
    Samavi, Shadrokh
    PROCEEDINGS OF THE 13TH IRANIAN/3RD INTERNATIONAL MACHINE VISION AND IMAGE PROCESSING CONFERENCE, MVIP, 2024, : 107 - 111
  • [10] A robust blind medical image watermarking approach for telemedicine applications
    Kahlessenane, Fares
    Khaldi, Amine
    Kafi, Redouane
    Euschi, Salah
    CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2021, 24 (03): : 2069 - 2082