By K. J. Ray Liu, Wade Trappe, Jane Z. Wang, Min Wu, Hong Zhao
The recognition of multimedia content material has ended in the common distribution and intake of electronic multimedia info. end result of the relative ease with which people might now regulate and repackage electronic content material, making sure that media content material is hired through approved clients for its meant function is turning into a topic of eminent significance to either governmental defense and advertisement functions. electronic fingerprinting is a category of multimedia forensic applied sciences to trace and establish entities fascinated by the unlawful manipulation and unauthorized utilization of multimedia content material, thereby preserving the delicate nature of multimedia information in addition to its advertisement worth after the content material has been brought to a recipient. "Multimedia Fingerprinting Forensics for Traitor Tracing" covers the basic points of analysis during this rising know-how, and explains the most recent improvement during this box. It describes the framework of multimedia fingerprinting, discusses the demanding situations which may be confronted whilst imposing utilization polices, and investigates the layout of fingerprints that do something about new households of multiuser assaults which may be fastened opposed to media fingerprints. The dialogue supplied within the booklet highlights difficult difficulties in addition to destiny traits during this examine box, delivering readers with a broader view of the evolution of the younger box of multimedia forensics.
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Additional resources for Multimedia Fingerprinting Forensics for Traitor Tracing (Eurasip Signal Processing and Communications)
In practical implementation, the orthogonality may be approximated by using random number generators to produce independent watermark signals for diﬀerent users. The orthogonality allows for distinguishing the fingerprints to the maximum extent. The simplicity of encoding and embedding orthogonal fingerprints makes them attractive to identification applications that involve a small group of users. One drawback of orthogonal fingerprints is that the amount of fingerprints is limited by the amount of orthogonal signals that can be created.
When λi is smaller, the trace of colluder i’s fingerprint is weaker and colluder i is less likely to be caught by the detector. In multiuser collusion, since no colluder would like to take more of a risk than any other colluder, they usually agree to distribute the risk of being detected evenly among themselves and apply fair collusion. A simple way to achieve the fairness of collusion is to average all the fingerprinted signals with an equal weight for each user and let λi = 1/K for all i. 1 shows an example of collusion by averaging with three colluders and all three fingerprints are averaged with the same weight 1/3.
P f p = 10−2 in (a) and γi = 10−2 in (b). 61) otherwise. 10 shows an example of the probability density function of a bounded Gaussian-like distribution. 9. Comparison of perceptual quality of the attacked images under diﬀerent attacks with 75 2 colluders. Fingerprints are generated from unbounded Gaussian distribution with σW = 1/9. (Left) Lena. (Right) Baboon. (Top) The zoomed-in region of the original 256 × 256 images. (Middle) The colluded images under the average attack. (Bottom) The colluded images under the minimum attack.
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