The perceptual quality of digital imagery is of great interest in many applications. Blur artifacts can be among the most
annoying in processed images and video sequences. In many applications of perceptual quality assessment, a reference is
not available. Therefore no-reference blurriness measures are of interest. In this paper, we present a universal, reference-free
blurriness measurement approach. While some other methods are designed for a particular source of blurriness such
as block-based compression, the proposed is universal in that it should work for any source of blur. The proposed
approach models the gradient image of the given image as Markov chain and utilizes transition probabilities to compute
a blurriness measure. This is the first time that transition probabilities are applied to perceptual quality assessment.
Specifically, we first compute the transition probabilities for selected pairs of gradient values and then combine these
probabilities, using a pooling strategy, to formulate the blurriness measure. Experimental studies compare the proposed
method to the state-of-the-art reference-free blurriness measurement algorithms and show that the proposed method
outperforms the commonly used measures.
KEYWORDS: Digital watermarking, Video, Sensors, Video compression, Chromium, Data processing, Computer programming, Image registration, Binary data, Data hiding
This work addresses the watermarking of an entropy coded H.264/AVC video stream. The phrase Substitution
Watermarking is used to imply that the application of the watermark to the stream is accomplished by substituting an
original block of bits in the entropy-encoded stream with an alternative block of bits. This substitution is done for many
different blocks of bits to embed the watermark. This can be a particularly powerful technique for applications in which
the embedder must be very simple (substitution is a very light operation) and a computationally complex, pre-embedding
analysis is practical. The pre-embedding analysis can generate a substitution table and the embedder can simply select
entries from the table based on the payload. This paper presents the framework along with an example for H.264/AVC
streams that use CAVLC for entropy coding. A separate paper addresses the CABAC entropy coding case.
Digital forensic marking is a technology to discourage unauthorized redistribution of multimedia signals by embedding a
unique mark into each user's copy of the content. A powerful class of attacks on forensic marking is the collusion attack
by a group of users. Recently, a new collusion attack, called the minority attack, has been proposed against forensic
marking schemes with correlation-based detectors. Although this attack is not very effective on Gaussian-based forensic
marking, it is quite powerful on removing the traces of users when the forensic marking is binary. In this paper, we first
study the performance of an ECC-based binary forensic code under the minority attack and we model the additional
processing, such as compression, applied on colluded copy as a binary symmetric channel. We confirm that the system
can be defeated by a minority attack from only 3 colluders. To resist the minority attack, we propose a row-permuted
binary orthogonal code to serve as the inner code for ECC-based forensic code, coupled with an adaptive detector.
Experimental results show that the proposed scheme has a significantly improved resistance to a minority attack.
There are two primary challenges to monitoring the Web for steganographic media: finding suspect media and examining those found. The challenge that has received a great deal of attention is the second of these, the steganalysis problem. The other challenge, and one that has received much less attention, is the search problem. How does the steganalyzer get the suspect media in the first place? This paper describes an innovative method and architecture to address this search problem. The typical approaches to searching the web for covert communications are often based on the concept of “crawling” the Web via a smart “spider.” Such spiders find new pages by following ever-expanding chains of links from one page to many next pages. Rather than seek pages by chasing links from other pages, we find candidate pages by identifying requests to access pages. To do this we monitor traffic on Internet backbones, identify and log HTTP requests, and use this information to guide our process. Our approach has the advantages that we examine pages to which no links exist, we examine pages as soon as they are requested, and we concentrate resources only on active pages, rather than examining pages that are never viewed.
KEYWORDS: Digital watermarking, Forensic science, Visualization, Video, Computer security, Modulation, Internet, Linear filtering, Visual process modeling, Information security
Forensic digital watermarking is a promising tool in the fight
against piracy of copyrighted motion imagery content, but to
be effective it must be (1) imperceptibly embedded in high-definition motion picture source, (2) reliably retrieved, even from degraded copies as might result from camcorder capture and subsequent very-low-bitrate compression and distribution on the Internet, and (3) secure against unauthorized removal. No existing watermarking technology has yet to meet these three simultaneous requirements of fidelity, robustness, and security. We describe here a forensic watermarking approach that meets all three requirements. It is based on the inherent robustness and imperceptibility of very low spatiotemporal frequency watermark carriers, and on a watermark placement technique that renders jamming attacks too costly in picture quality, even if the attacker has complete knowledge of the embedding algorithm. The algorithm has been tested on HD Cinemascope source material exhibited in a digital cinema viewing room. The
watermark is imperceptible, yet recoverable after exhibition capture with camcorders, and after the introduction of other distortions such as low-pass filtering, noise addition, geometric shifts, and the manipulation of brightness and contrast.
KEYWORDS: Digital watermarking, Sensors, Fourier transforms, Databases, Signal to noise ratio, Image registration, Pattern recognition, Image processing, Signal processing, Signal detection
Many electronic watermarks for still images and video content are sensitive to geometric distortions. For example, simple rotation, scaling, and/or translation (RST) of an image can prevent detection of a public watermark. In this paper, we propose a watermarking algorithm that is robust to RST distortions. The watermark is embedded into a 1-dimensional signal obtained by first taking the Fourier transform of the image, resampling the Fourier magnitudes into log-polar coordinates, and then summing a function of those magnitudes along the log-radius axis. If the image is rotated, the resulting signal is cyclically shifted. If it is scaled, the signal is multiplied by some value. And if the image is translated, the signal is unaffected. We can therefore compensate for rotation with a simple search, and for scaling by using the correlation coefficient for the detection metric. False positive results on a database of 10,000 images are reported. Robustness results on a database of 2,000 images are described. It is shown that the watermark is robust to rotation, scale and translation. In addition, the algorithm shows resistance to cropping.
In order to recognize an arbitrary 3D object, it is often required to extract feature points
and feature lines from its surface model. The feature points and feature lines include peaks,
pits, ridge lines, and valley lines. In this paper, we present an efficient technique for finding the
features from the triangular surface model of an arbitrary 3D object. Given a set of surface
data points, we find, using the local adjustment technique, the triangular patches that best fit
the surface of the object. For the resulting triangle-based surface model, unit normal vectors
and side lengths of the triangular patches are used systematically to locate the feature points
and lines of the surface. We present experimental results on simple objects with feature points
and feature lines.
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