In this paper, we propose a semi-blind video watermarking scheme, where we use pseudo-random robust semi-global features of video in the spatially wavelet transform domain. We design the watermark sequence via solving an optimization problem, such that the features of the mark-embedded video are the quantized versions of the features of the original video. We use a novel approach in generating the watermark such that the temporal correlation within the video frames is reflected on the generated watermark. This is achieved by i) using a special weight distribution along the time axis ii) modifying the regularization step to reflect the temporal characteristic of the host. We experimentally show the robustness of our algorithm against temporal filtering attacks and at the same time show a common weakness in 3D transform based video mark embedding methods.
KEYWORDS: Video, Digital watermarking, Receivers, Quantization, Sensors, Prisms, Optimization (mathematics), Video compression, Information security, Signal detection
In this paper, we propose a novel semi-blind video watermarking scheme, where we use pseudo-random robust semi-global features of video in the three dimensional wavelet transform domain. We design the watermark sequence via solving an optimization problem, such that the features of the mark-embedded video are the quantized versions of the features of the original video. The exact realizations of the algorithmic parameters are chosen pseudo-randomly
via a secure pseudo-random number generator, whose seed is the secret key, that is known (resp. unknown) by the embedder and the receiver (resp. by the public). We experimentally show the robustness of our algorithm against several attacks, such as conventional signal processing modifications and adversarial estimation attacks.
KEYWORDS: Video, Receivers, Digital watermarking, Computer programming, Forensic science, Video surveillance, Cryptography, Sensors, Digital forensics, Information security
In this paper, we concentrate on video watermarking for forensics applications and consider the temporal synchronization problem, which has been overlooked in the literature so far. As a result,
we propose a system that provides temporal synchronization in video
watermarking by using side information at the receiver. Short perceptually-robust representations (also known as robust hash values) of randomly selected frames from the watermarked video regions is derived at the encoder and transmitted to the decoder. Synchronization is then achieved by computing perceptually-representative information of all frames of the received video
at the receiver and finding the "best matching region" via solving
a combinatorial optimization problem efficiently using dynamic programming techniques. A suitably-chosen "robust image hash" function is used to derive the necessary representative information of the video frames; the resulting hash values possess properties of being short in length, computable in real time, and similar (resp. different) for perceptually similar (resp. different) video frames with high probability. We experimentally illustrate the effectiveness of our method against several attacks, which include frame-wise geometric attacks, as well as temporal de-synchronization attacks, such as random temporal interpolation, scene editing, cutting and swapping.
In this paper, we study the problem of optimizing slice sizes and locations for video transmission over bit error channels. We propose a method that utilizes estimation of slice rate and distortion which is a function of the inter-macroblock dependency as exploited in the video codec. First we experimentally show that our estimation is effective. Since there are practically numerous possibilities for slice configurations and one must actually check all possibilities for a complete search, we assume segmentation of macroblocks so that a slice can only start at the segments. Although this results in a slightly suboptimal solution, it reduces the number of possibilities. However there are still practically too many configurations. Then we use the proposed RD estimation method and combine it with a dynamic programming approach to effectively determine the most optimal slice configuration. RD optimization is carried out in terms of minimizing the expected Lagrangian using the expected distortion of a slice. We assume that the physical layer is capable of generating an error report showing which transmission units are received in error. This allows us to use NEWPRED with macroblock level feedback and prevent wrongful decoding of erroneous macroblocks. We compare the proposed system with the two common approaches namely, fixed number of MBs per slice and fixed number of bits per slice and see that the proposed method performs better than both.
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