Robust image watermarking via geometrically invariant feature points and image normalisation

Nasir, Ibrahim, Khelifi, Fouad, Jiang, Jianmin and Ipson, Stanley (2012) Robust image watermarking via geometrically invariant feature points and image normalisation. IET Image Processing, 6 (4). pp. 354-363. ISSN 1751-9659

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The robustness of watermarks to geometric attacks is viewed as an issue of great importance. Indeed, it constitutes one of the most challenging design requirements for watermarks. This study proposes a robust image watermarking scheme using visually significant feature points and image normalisation. In order to tackle the issue of geometric distortions, the authors adopt a feature extraction method based on end-stopped wavelets to extract significant geometry preserving feature points, which are shown to be robust against various types of common signal processing and geometric attacks. These feature points can be used as synchronisation marks between watermark embedding and detection. The watermark is embedded into non-overlapping normalised circular images, which are determined by feature points. Rotation invariance is achieved via image normalisation. The watermark embedding process is performed by modifying low-frequency coefficients of discrete cosine transform blocks, which are randomly selected using a secret key. Moreover, the security of the scheme is further guaranteed by an image-dependent key. The proposed scheme is blind as the original image is not required at the watermark detection. Experimental results show that the proposed scheme is robust against geometric attacks as well as common signal processing attacks and outperforms related techniques found in the literature.

Item Type: Article
Uncontrolled Keywords: discrete cosine transforms, distortion, image watermarking, object detection, feature extraction
Subjects: H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: Ellen Cole
Date Deposited: 21 Dec 2012 14:00
Last Modified: 12 Oct 2019 19:07

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