Content-based Watermarking Scheme Research Articles

Authentication of DICOM medical images using independent component analysis (ICA)

This paper proposes a blind content-based watermarking scheme for image authentication using ICA and DCT. The watermark to be embedded is obtained from the host image itself in terms of the Frobenius norm of the mixing matrix obtained during ICA. These are embedded in the mid-frequency DCT coefficients. The proposed method correctly authenticates the image even under normal image processing operations and it correctly detects tampering and identifies the tampered regions of the image. The average PSNR value in this proposed ICA-based technique is around 97 which makes it superior than the existing watermarking techniques.

Semi-Fragile Zernike Moment-Based Image Watermarking for Authentication

We propose a content-based semi-fragile watermarking algorithm for image authentication. In content-based watermarking scheme for authentication, one of the most challenging issues is to define a computable feature vector that can capture the major content characteristics. We identify Zernike moments of the image to generate feature vector and demonstrate its good robustness and discriminative capability for authentication. The watermark is generated by quantizing Zernikemoments magnitudes (ZMMs) of the image and embedded into DWT (Discrete Wavelet Transform) subband. It is usually hard to locate the tampered area by using global feature in the content-based watermarking scheme. We propose a structural embedding method to locate the tampered areas by using the separability of Zernike moments-based feature vector. The authentication process does not need the original feature vector. By using the semi-fragilities of the feature vector and the watermark, the proposed authentication scheme is robust to content-preserved processing, while being fragile to malicious attacks. As an application of our algorithm, we apply it on Chinese digital seals and the results show that it works well. Compared with some existing algorithms, the proposed scheme achieves better performance in discriminating high-quality JPEG compression from malicious attacks.

A local Tchebichef moments-based robust image watermarking

Protection against geometric distortions and common image processing operations with blind detection becomes a much challenging task in image watermarking. To achieve this, in this paper we propose a content-based watermarking scheme that combines the invariant feature extraction with watermark embedding by using Tchebichef moments. Harris-Laplace detector is first adopted to extract feature points, and then non-overlapped disks centered at feature points are generated. These disks are invariant to scaling and translation distortions. For each disk, orientation alignment is then performed to achieve rotation invariant. Finally, the watermark is embedded in magnitudes of Tchebichef moments of each disk via dither modulation to realize the robustness to common image processing operations and the blind detection. Thorough simulation results obtained by using the standard benchmark, Stirmark, demonstrate that the proposed method is robust against various geometric distortions as well as common image processing operations and outperforms representative image watermarking schemes.

Geometrically invariant watermarking using feature points

This paper presents a new approach for watermarking of digital images providing robustness to geometrical distortions. The weaknesses of classical watermarking methods to geometrical distortions are outlined first. Geometrical distortions can be decomposed into two classes: global transformations such as rotations and translations and local transformations such as the StirMark attack. An overview of existing self-synchronizing schemes is then presented. Theses schemes can use periodical properties of the mark, invariant properties of transforms, template insertion, or information provided by the original image to counter geometrical distortions. Thereafter, a new class of watermarking schemes using the image content is presented. We propose an embedding and detection scheme where the mark is bound with a content descriptor defined by salient points. Three different types of feature points are studied and their robustness to geometrical transformations is evaluated to develop an enhanced detector. The embedding of the signature is done by extracting feature points of the image and performing a Delaunay tessellation on the set of points. The mark is embedded using a classical additive scheme inside each triangle of the tessellation. The detection is done using correlation properties on the different triangles. The performance of the presented scheme is evaluated after JPEG compression, geometrical attack and transformations. Results show that the fact that the scheme is robust to these different manipulations. Finally, in our concluding remarks, we analyze the different perspectives of such content-based watermarking scheme.