Fast watermarking of MPEG-1/2 streams using compressed-domain perceptual embedding and a generalized correlator detector

A novel technique is proposed for watermarking of MPEG-1 and MPEG-2 compressed video streams. The proposed scheme is applied directly in the domain of MPEG-1 system streams and MPEG-2 program streams (multiplexed streams). Perceptual models are used during the embedding process in order to avoid degradation of the video quality. The watermark is detected without the use of the original video sequence. A modified correlation-based detector is introduced that applies nonlinear preprocessing before correlation. Experimental evaluation demonstrates that the proposed scheme is able to withstand several common attacks. The resulting watermarking system is very fast and therefore suitable for copyright protection of compressed video

Embedding Strength Criteria for AWGN Watermark, Robust Against Expected Distortion

In this paper we engage in AWGN watermark for grayscale image (the message is embedded by adding of white Gaussian noise matrix; detection is blind, correlation based). We search criteria for ``the best'' (minimal one which guaranties watermark detectability) embedding strength for watermark robust against expected attack. These criteria we find for AWGN watermarks, which are embedded in spatial or in transform domains; for one bit message or for a longer message; into whole image or into some of its coefficients. This paper peculiarity is that we do not propose new watermarking algorithm; for well known, robust algorithm we find the best embedding strength for robust watermark

Towards Optimal Copyright Protection Using Neural Networks Based Digital Image Watermarking

In the field of digital watermarking, digital image watermarking for copyright protection has attracted a lot of attention in the research community. Digital watermarking contains varies techniques for protecting the digital content. Among all those techniques,Discrete Wavelet Transform (DWT) provides higher image imperceptibility and robustness. Over the years, researchers have been designing watermarking techniques with robustness in mind, in order for the watermark to be resistant against any image processing techniques. Furthermore, the requirements of a good watermarking technique includes a tradeoff between robustness, image quality (imperceptibility) and capacity. In this paper, we have done an extensive literature review for the existing DWT techniques and those combined with other techniques such as Neural Networks. In addition to that, we have discuss the contribution of Neural Networks in copyright protection. Finally we reached our goal in which we identified the research gaps existed in the current watermarking schemes. So that, it will be easily to obtain an optimal techniques to make the watermark object robust to attacks while maintaining the imperceptibility to enhance the copyright protection

Wavelet İle Dayanıklı Mpeg Video Damgalama

DergiPark: 245960trakyafbdYarı kör resim damgalama metodu PRN sayılarını DWT HH bant katsayılarından T1 basamağından büyük olanlarına damgalar. Saldırıya uğramış resim katsayıları başlangıç resim ile korelasyon yapılır. Damgayı bulmak için, basamak T2’den (T2 gt; T1 ) büyük olan katsayılar başlangıç resmi ile korelasyon edilir. Bu fikir LL ve HH bantlarına damgalama olarak geliştirilmiştir. Bu makalede ise bu daha önce geliştirdiğimiz bu fikri MPEG videoları için kullandık. Deney sonuçlarımız gösteriyorki bazı saldırılar için LL bantında damgalama, diğer bir grup saldırıda ise HH bantında damgalama daha iyi sonuç vermektedir.A semi-blind image watermarking scheme embeds a pseudo random sequence in all the high pass DWT coefficients above a given threshold T1. The attacked DWT coefficients are then correlated with the original watermark. For watermark detection, all the coefficients higher than another threshold T2 ( gt;T1) are chosen for correlation with the original watermark. This idea was extended to embed the same watermark in two bands (LL and HH). In this paper, we embed a pseudo random sequence in MPEG-1 using two bands (LL and HH). Our experiments show that for one group of attacks (i.e., JPEG compression, Gaussian noise, resizing, low pass filtering, rotation, and frame dropping), the correlation with the real watermark is higher than the threshold in the LL band, and for another group of attacks (i.e., cropping, histogram equalization, contrast adjustment, and gamma correction), the correlation with the real watermark is higher than the threshold in the HH band