The VIVA project: digital watermarking for broadcast monitoring

Depovere, G.; Kalker, Ton; Haitsma, Jaap; Maes, M.; Strycker, Lieven De; Termont, P.; Vandewege, Jan; Langell, A.; Alm, Cecilia Ovesdotter; Norman, Patrick; O'Reilly, Gerard P.; Howes, B.; Vaanholt, H.; Hintzen, R.; Donnelly, Patrick J.; Hudson, Adam

doi:10.1109/icip.1999.822884

Cited by 27 publications

(14 citation statements)

References 4 publications

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“…On the other hand, methods of using digital watermarking techniques to embed the material ID code in an image have also been investigated [4][5][6][7]. These methods can be applied even on various types of equipment that do not guarantee that vertical blanking data will be saved.…”

Section: Introductionmentioning

confidence: 98%

“…To take requirement (b) into consideration, conventional methods [4][5][6] use data extraction algorithms that assume there is an uncorrelation between the image and a pseudo-noise pattern that is embedded. However, there exist many images for which this uncorrelation assumption does not hold, and in those cases, data extraction ends up being difficult [8].…”

Section: Introductionmentioning

confidence: 99%

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A watermarking scheme without reference images for broadcast monitoring

Tachibana¹,

Fujiyoshi²,

Kiya³

2004

Electron Comm Jpn Pt III

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SUMMARYIn this paper, to automate broadcast monitoring, which is typified by the verification of the transmission of the material ID code of a commercial message (CM) or program, the authors propose a watermarking scheme without reference images, which does not require a reference image when the watermark sequence is extracted. By embedding a watermark sequence formed by using standard normal random numbers after discretizing the embeddingtarget coefficients in the DCT domain, the proposed technique makes a reference image unnecessary when the watermark sequence is extracted. In addition, since the proposed technique enables a watermark image having the desired image quality (PSNR) to be achieved for any image, it has the advantage that the image quality can always be maintained regardless of the image. Therefore, the same procedure can always be used to embed the watermark sequence in a full-motion video image without obtaining parameters for each image and to extract that watermark sequence without using a reference image. The authors used simulations to verify that an image quality of at least 56 dB, which is the HDTV digital VTR guideline, can be maintained even in the watermarked image, that the watermark sequence can be extracted without using a reference image, and that the proposed technique is robust with respect to MPEG.

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Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

A watermarking scheme without reference images for broadcast monitoring

Tachibana¹,

Fujiyoshi²,

Kiya³

2004

Electron Comm Jpn Pt III

View full text Add to dashboard Cite

show abstract

“…The most sophisticated method to accomplish this in present years is digital watermarking [1][2][3]. It is interesting to note that it has since been also used in the context of other applications such as integrity checking [4,5], broadcast monitoring [6,7] and fingerprinting [8,9]. When referring to the design of a watermarking algorithm for copyright protection of digital images, there are certain requirements that we would like it to meet [10]:…”

Section: Introductionmentioning

confidence: 99%

Local distortion resistant image watermarking relying on salient feature extraction

Nikolaidis

2012

EURASIP J. Adv. Signal Process.

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The purpose of this article is to present a novel method for region based image watermarking that can tolerate local image distortions to a substantially greater extent than existing methods. The first stage of the method relies on computing a normalized version of the original image using image moments. The next step is to extract a set of feature points that will act as centers of the watermark embedding areas. Four different existing feature extraction techniques are tested: Radial Symmetry Transform (RST), scale-invariant feature transform (SIFT), speeded up robust features (SURF) and features from accelerated segment test (FAST). Instead of embedding the watermark in the DCT domain of the normalized image, we follow the equivalent procedure of first performing the inverse DCT of the original watermark, inversely normalizing it and finally embedding it in the original image. This is done in order to minimize image distortion imposed by inversely normalizing the normalized image to obtain the original. The detection process consists of normalizing the input image and extracting the feature points of the normalized image, after which a correlation detector is employed to detect the possibly inserted watermark in the normalized image. Experimental results demonstrate the relative performance of the four different feature extraction techniques under both geometrical and signal processing operations, as well as the overall superiority of the method against two state-of-the-art techniques that are quite robust as far as local image distortions are concerned.

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“…Temper detection [22], copyright control [4], owner identification [6], broadcast monitoring [11], etc., are some of the interesting examples of watermarking applications.…”

Section: Introductionmentioning

confidence: 99%

Protection of medical images and patient related information in healthcare: Using an intelligent and reversible watermarking technique

Arsalan

Qureshi

Khan

et al. 2017

Applied Soft Computing

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Rajarajan, M. (2017). Protection of medical images and patient related information in healthcare: Using an intelligent and reversible watermarking technique. Applied Soft Computing Journal, 51, pp. 1668-179. doi: 10.1016/j.asoc.2016.11.044 This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent AbstractThis work presents an intelligent technique based on reversible watermarking for protecting patient and medical related information. In the proposed technique 'IRW-Med', the concept of companding function is exploited for reducing embedding distortion, while Integer Wavelet Transform (IWT) is used as an embedding domain for achieving reversibility. Histogram processing is employed to avoid underflow/overflow. In addition, the learning capabilities of Genetic Programming (GP) are exploited for intelligent wavelet coefficient selection. In this context, GP is used to evolve models that not only make an optimal tradeoff between imperceptibility and capacity of the watermark, but also exploit the wavelet coefficient hidden dependencies and information related to the type of sub band. The novelty of the proposed IRW-Med technique lies in its ability to generate a model that can find optimal wavelet coefficients for embedding, and also acts as a companding factor for watermark embedding. The proposed IRW-Med is thus able to embed watermark with low distortion, take out the hidden information, and also recovers the original image. The proposed IRW-Med technique is effective with respect to capacity and imperceptibility and effectiveness is demonstrated through experimental comparisons with existing techniques using standard images as well as a publically available medical image dataset.

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The VIVA project: digital watermarking for broadcast monitoring

Cited by 27 publications

References 4 publications

A watermarking scheme without reference images for broadcast monitoring

A watermarking scheme without reference images for broadcast monitoring

Local distortion resistant image watermarking relying on salient feature extraction

Protection of medical images and patient related information in healthcare: Using an intelligent and reversible watermarking technique

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