4.6 Article

Local quaternion PHT based robust color image watermarking algorithm

Journal

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jvcir.2016.04.011

Keywords

Color image watermarking; Desynchronization attacks; SIFER detector; Color invariance model; Algebra of quaternions; Polar harmonic transform

Funding

  1. National Natural Science Foundation of China [61472171, 61272416]
  2. Liaoning Research Project for Institutions of Higher Education of China [L2013407]

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It is a challenging work to design a robust localized color image watermarking scheme against desynchronization attacks. There are two main drawbacks indwelled in current localized color image watermarking: firstly, the pure gray-based feature points detectors were utilized, in which the important color information is ignored. Secondly, the watermarking algorithms were designed mainly to mark the image luminance component only, in which the significant color channels correlation are neglected. In this paper, we propose a robust color image watermarking algorithm using local quaternion PHT (Polar Harmonic Transform), which is invariant to various noises, local geometric transformations, and color variations. Firstly, the stable color image feature points are extracted by using new color image feature point detector, in which the SIFER (Scale-Invariant Feature detector with Error Resilience) detector and color invariance model are incorporated. Then, the affine invariant local regions are built adaptively according to local image content variation. Finally, the digital watermark is embedded into the local regions by modulating the invariant quaternion PHT modulus coefficients. Experiments are carried out on a color image set collected from Internet, and the extensive experimental works have shown that the proposed color image watermarking is not only invisible and robust against common image processing operations such as median filtering, noise adding, and JPEG compression, but also has conquered those challenging desynchronization attacks. (C) 2016 Elsevier Inc. All rights reserved.

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