Robust Wavelet-Based Facial Image Watermarking Against Geometric Attacks Using Coordinate System Recovery

A coordinate system of the original image is established using a facial feature point localization technique. After the original image transformed into a new image with the standard coordinate system, a redundant watermark is adaptively embedded in the discrete wavelet transform（DWT） domain based on the statistical characteristics of the wavelet coefficient block. The coordinate system of watermarked image is reestablished as a calibration system. Regardless of the host image rotated, scaled, or translated（RST）, all the geometric attacks are eliminated while the watermarked image is transformed into the standard coordinate system. The proposed watermark detection is a blind detection. Experimental results demonstrate the proposed scheme is robust against common and geometric image processing attacks, particularly its robustness against joint geometric attacks.

NEW APPROACH TO COPYRIGHT PROTECTION OF IMAGE AGAINST GEOMETRICAL ATTACKS

To protect the copyright of the image as well as the image quality, a kind of image zero-watermark method based on the Krawtchouk moment invariants and timestamp is proposed. A method is used to protect the image, in which features are drawn out from the image as the watermarking. The main steps of the method are presented. Firstly, some low-order moment invariants of the image are extracted. Secondly, the moment invariants and the key are registered to a fair third party to gain the timestamp. Finally, the timestamp can be used to prove who the real owner is. The processing method is simple, only with a few low-order moment invariants to be computed. Experimental results are obtained and compared with those of the method based on geometric moment invariants. Results show that the scheme can well withstand such geometrical attacks as rotating, scaling, cropping, combined attack, translating, removing lines, filtering, and JPEG lossy compression.

Difference Energy Based Blind Image Watermarking Resisting to Geometrical Distortions

In this paper a blind image watermarking that can resist to rotation, scaling and translation （RST） attacks is proposed. Based on the spread spectrum, the watermark is modulated before embedding. The logpolar mapped discrete fourier transform （LPM-DFT） magnitude of a disk, a part of the origin image, constitutes the RST-invariant domain, where the origin of the LPM is the center of the disk and the sampling rates of the LPM are constant. After the middle frequency band of LPM-DFT magnitude, namely the watermark-embedding domain, is grouped according to the watermark length, the watermark is embedded by adjusting the difference between the two sub-region energy in each group. To improve the imperceptibility, the watermark-embedding domain is shuffled before embedding and the watermark is not embedded directly into the watermark-embedding domain. In watermark detection procedure, neither the original image nor any knowledge about the distortions is required. Experimental results show that the proposed scheme is very robust against RST distortion and common image processing attacks.

Image-Moment Based Affine Invariant Watermarking Scheme Utilizing Neural Networks

A new image watermarking scheme is proposed to resist rotation, scaling and translation （RST） attacks. Six combined low order image moments are utilized to represent image information on rotation, scaling and translation. Affine transform parameters are registered by feedforward neural networks. Watermark is adaptively embedded in discrete wavelet transform （DWT） domain while watermark extraction is carried out without original image after attacked watermarked image has been synchronized by making inverse transform through parameters learned by neural networks. Experimental results show that the proposed scheme can effectively register affine transform parameters, embed watermark more robustly and resist geometric attacks as well as JPEG2000 compression.

SYNCHRONIZATION RECOVERY SCHEME IN WATERMARKING DETECTION

Most proposed digital watermarking algorithms are sensitive to geometric attacksbecause the synchronization information of watermark embedding and detection is destroyed. Inthis letter a novel synchronization recovery scheme based on image normalization is proposed. Thepresented scheme does not require the original image and can be applied to various watermarksystems. A wavelet-based watermarking scheme is proposed as an example and experimentalresults show that it is robust to geometric attacks.

Robust Image Watermarking Using Local Invariant Features and Independent Component Analysis

This paper proposes a novel robust image watermarking scheme for digital images using local invariant features and Independent Component Analysis （ICA）. Most present watermarking algorithms are unable to resist geometric distortions that desynchronize the location. The method we propose here is robust to geometric attacks. In order to resist geometric distortions, we use a local invariant feature of the image called the scale invariant feature transform, which is invariant to translation and scaling distortions. The watermark is inserted into the circular patches generated by scale-invariant key point extractor. Rotation invariance is achieved using the translation property of the polar-mapped circular patches. Our method belongs to the blind watermark category, because we use Independent Component Analysis for detection that does not need the original image during detection. Experimental results show that our method is robust against geometric distortion attacks as well as signal-processing attacks.

An adaptive blind watermarking scheme utilizing neural network for synchronization

An important problem constraining the practical implementation of robust watermarking technology is the low robustness of existing algorithms against geometrical distortions. An adaptive blind watermarking scheme utilizing neural network for synchronization is proposed in this paper,which allows to recover watermark even if the image has been subjected to generalized geometrical transforms. Through classification of image’s brightness, texture and contrast sensitivity utilizing fuzzy clustering theory and human visual system, more robust watermark is adaptively embedded in DWT domain. In order to register rotation, scaling and translation parameters, feedforward neural network is utilized to learn image geometric pattern represented by six combined low order image moments. The distortion can be inverted after determining the affine distortion applied to the image and watermark can be extracted in a standard way without original image. It only needs a trained neural network. Experimental results demonstrate its advantages over previous method in terms of computational effectiveness and parameter estimation accuracy. It can embed more robust watermark under certain visual distance, and effectively resist JPEG compression, noise and geometric attacks.

Geometrically robust video water-marking based on wavelet transform

Geometrical attacks can destroy most watermarking systems at present. So how to efficiently resist such kind of attacks remains a challenging direction in watermarking research. In this paper, a novel sequence watermarking scheme, which exploits a geometrical invariant, i.e. average AC energy （AAE） to combat arbitrary geometrical attacks, is presented. The scheme also uses some other measures, such as synchronization and optimal whitening filter to resist other attacks and improve detection performance. The experimental results show that the scheme can efficiently improve the visual quality of the watermarked video and achieve good robustness against random geometrical attacks. The scheme also has good robustness against other attacks, such as low-pass filtering along time axis and frame removal.

Watermarking through image geometry change tracking

Most of the digital image watermarking techniques are susceptible to geometric attacks such as cropping,rotation and scaling.These attacks are the easiest yet most successful in rendering the survival of watermark difficult.Such geometric operations alter the pixel orientation in the cover thereby rendering the watermark difficult to locate and extract.However,if the alterations produced by the geometric attacks such as scaling,cropping and rotation can be modeled in terms of the change in the image geometry,it is possible to relocate the watermark even after the original cover has suffered an attack.This paper contributes to the state of the art by proposing an image watermarking technique that attempts to model the attacks like cropping,scaling and rotation in terms of the image geometry.The proposed scheme is acceptably resistant to common geometric attacks and common image processing attacks.The watermark embedding is also done efficiently to offer resistance to image processing attacks.The watermark detection procedure is blind and key based,also not requiring the original cover work for watermark extraction.Efforts have been given to ensure that the proposed scheme conforms to robustness against attacks and exhibits high visual fidelity of the watermarked cover.

Rotation,scaling and translation invariant image watermarking using feature points

In this article, a novel robust image watermarking scheme is presented to resist rotation, scaling, and translation （RST）. Initially, the original image is scale normalized, and the feature points are then extracted. Furthermore, the locally most stable feature points are used to generate several nonoverlapped circular regions. These regions are then rotation normalized to generate the invariant regions. Watermark embedding and extraction are implemented in the invariant regions in discrete cosine transform domain. In the decoder, the watermark can be extracted without the original image. Simulation results show that the proposed scheme is robust to traditional signal processing attacks, RST attacks, as well as some combined attacks.