Invariant image watermarking based on statistical features in the low-frequency domain

Shijun Xiang, Hyoung Joong Kim, Jiwu Huang

    Research output: Contribution to journalArticlepeer-review

    158 Citations (Scopus)

    Abstract

    Watermark resistance to geometric attacks is an important issue in the image watermarking community. Most countermeasures proposed in the literature usually focus on the problem of global affine transforms such as rotation, scaling and translation (RST), but few are resistant to challenging cropping and random bending attacks (RBAs). The main reason is that in the existing watermarking algorithms, those exploited robust features are more or less related to the pixel position. In this paper, we present an image watermarking scheme by the use of two statistical features (the histogram shape and the mean) in the Gaussian filtered low-frequency component of images. The two features are: 1) mathematically invariant to scaling the size of images; 2) independent of the pixel position in the image plane; 3) statistically resistant to cropping; and 4) robust to interpolation errors during geometric transformations, and common image processing operations. As a result, the watermarking system provides a satisfactory performance for those content-preserving geometric deformations and image processing operations, including JPEG compression, lowpass filtering, cropping and RBAs.

    Original languageEnglish
    Article number4454287
    Pages (from-to)777-790
    Number of pages14
    JournalIEEE Transactions on Circuits and Systems for Video Technology
    Volume18
    Issue number6
    DOIs
    Publication statusPublished - 2008 Jun

    Bibliographical note

    Funding Information:
    Manuscript received April 17, 2007; revised July 25, 2007, September 24, 2007, and December 23, 2007. This work was supported in part by the National Science Foundation of China under Grant 60325208, Grant 90604008, and Grant 60633030, in part by the National Science Foundation of Guangdong under Grant 04205407, 973 Program 2006CB303104, China, in part by the Second Brain Korea 21 Project, and in part by the the ITRC program of MIC/IITA, and the IT R&D program of MIC/IITA [2008-F-036-01]. This paper was recommended by Associate Editor M. Barni.

    Keywords

    • Cropping
    • Gaussian filter
    • Histogram
    • Image watermarking
    • Random bending attacks

    ASJC Scopus subject areas

    • Media Technology
    • Electrical and Electronic Engineering

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