We propose an improved autocorrelation function (ACF)-based image watermarking that is robust to combined geometric and removal attacks. ACF-based watermarking is thought of as one of the most effective watermarking schemes that resist geometric attacks. In this watermarking scheme, the autocorrelation peaks of the watermark play an important role for geometric attack estimation. The peaks, however, are vulnerable to attacks. The proposed scheme enhances the performance of ACF-based watermarking by improving the strength of the peaks. The information of an original image is used at the embedding time, so that the detector can extract strong autocorrelation peaks. Experimental results show that the proposed scheme yields better robustness than conventional ACF based watermarking against combined geometric-removal attacks.
In this paper, we propose an improved autocorrelation function
(ACF) based watermarking. The autocorrelation function based
watermarking has been known to be one of the effective
watermarking schemes that are resilient to geometric transform
attacks. In this watermarking scheme, both the peaks in the
autocorrelation function of a marked image and the embedded
watermark should survive after various attacks. Generally, the
autocorrelation peaks are less robust than the actual watermark
signal. The main focus of this paper is the improvement of the
robustness of the peaks in an autocorrelation function. Since an
original image and the detector structure are available at the
embedding time, instead of simple addition of a watermark to an
image, the watermark embedder analyzes the original image and uses
this information actively during the embedding process so that the
marked image has higher periodic autocorrelation peaks. The
proposed watermarking scheme has higher robustness than a
conventional ACF based watermarking against geometric attacks that
are combined with removal attacks.
In this paper, we present a method for protection of digital contents by using the watermark embedding in special object, especially, human faces. To insert the watermark signals that are composed of noise like binary signals, we first localize the face regions within images by using the color and edge information. The skin color area is filtered out and then edge detector is applied for skin area to find out face features. These features are used for decision whether the skin area is face region or not. The face region is divide non-overlapping sub-blocks and a watermark bit is inserted into the each sub- block by considering the block activity. We insert a watermark bit in DCT domain of each sub-block. The level of modification of the DCT coefficients is determined considering the block variance. The non-zero coefficients of the DCT are selected and modified according to the robustness levels. Then, inverse DCT is performed. The extraction of the watermark is performed by comparing the original image in DCT domain. The robustness of the watermarking is similar to the other methods in DCT, but it has good visual qualities and less intended external piracy in terms of psychology.
KEYWORDS: Digital watermarking, Video, Visualization, Video compression, Wavelet transforms, Multimedia, Wavelets, Visibility, Video processing, Information technology
This paper presents an adaptive video watermarking using motion information. Because video data have one more dimension than image data, simple adaptation of image watermarking method to video data would reveal some types of visual artifact such as flickering. In the proposed scheme, same watermark information is embedded for same region in each frame to decrease such visual artifact. For higher robustness and invisibility, watermarking strength is adjusted by motion information and region complexity.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.