KEYWORDS: Optical character recognition, Modulation, Printing, Binary data, Visualization, Data storage, Quantization, Digital watermarking, Computer programming, Data communications
In this paper, we deal with the problem of authentication and tamper-proofing of text documents that can be distributed in electronic or printed forms. We advocate the combination of robust text hashing and text data-hiding technologies as an efficient solution to this problem. First, we consider the problem of text data-hiding in the scope of the Gel'fand-Pinsker data-hiding framework. For illustration, two modern text data-hiding methods, namely color index modulation (CIM) and location index modulation (LIM), are explained. Second, we study two approaches to robust text hashing that are well suited for the considered problem. In particular, both approaches are compatible with CIM and LIM. The first approach makes use of optical character recognition (OCR) and a classical cryptographic message authentication code (MAC). The second approach is new and can be used in some scenarios where OCR does not produce consistent results. The experimental work compares both approaches and shows their robustness against typical intentional/unintentional document distortions including electronic format conversion, printing, scanning, photocopying, and faxing.
In this paper we consider the problem of document authentication in electronic and printed forms. We formulate this problem from the information-theoretic perspectives and present the joint source-channel coding theorems showing the performance limits in such protocols. We analyze the security of document authentication methods and present the optimal attacking strategies with corresponding complexity estimates that, contrarily to the existing studies, crucially rely on the information leaked by the authentication protocol. Finally, we present the results of experimental validation of the developed concept that justifies the practical efficiency of the elaborated framework.
KEYWORDS: Quantization, Halftones, Printing, Computer programming, Modulation, Digital watermarking, Scanners, Data conversion, Demodulation, Visual system
In this paper, we propose a new theoretical framework for the data-hiding problem of digital and printed text documents. We explain how this problem can be seen as an instance of the well-known Gel'fand-Pinsker problem. The main idea for this interpretation is to consider a text character as a data structure consisting of multiple quantifiable features such as shape, position, orientation, size, color, etc. We also introduce color quantization, a new semi-fragile text data-hiding method that is fully automatable, has high information embedding rate, and can be applied to both digital and printed text documents. The main idea of this method is to quantize the color or luminance intensity of each character in such a manner that the human visual system is not able to distinguish between the original and quantized characters, but it can be easily performed by a specialized reader machine. We also describe halftone quantization, a related method that applies mainly to printed text documents. Since these methods may not be completely robust to printing and scanning, an outer coding layer is proposed to solve this issue. Finally, we describe a practical implementation of the color quantization method and present experimental results for comparison with other existing methods.
In this paper we introduce and develop a framework for document interactive navigation in multimodal databases. First, we analyze the main open issues of existing multimodal interfaces and then discuss two applications that include interaction with documents in several human environments, i.e., the so-called smart rooms. Second, we propose a system set-up dedicated to the efficient navigation in the printed documents. This set-up is based on the fusion of data from several modalities that include images and text. Both modalities can be used as cover data for hidden indexes using data-hiding technologies as well as source data for robust visual hashing. The particularities of the proposed robust visual hashing are described in the paper. Finally, we address two practical applications of smart rooms for tourism and education and demonstrate the advantages of the proposed solution.
In this paper we consider the problem of performance improvement of known-host-state (quantization-based) watermarking methods undergo additive white Gaussian noise (AWGN) and uniform noise attacks. We analyze the underlying assumptions used for design of Dither Modulation (DM) and Distortion Compensated Dither Modulation (DC-DM) methods and question the optimality of high rate uniform quantizer based embedding into real images from the point of view of robustness of these methods to the selected additive attacks in terms of bit error rate probability. Motivated by superior performance of uniform deadzone quantizer (UDQ) over the uniform one in lossy transform based source coding, we propos to replace the latter one by the UDQ in data-hiding set-up designed according to the statistics of the host data that are assumed to be independent identically distributed Laplacian. Based on the suggested modifications we obtained analytical expressions for bit error rate probability analysis of host-statistics-dependent quantization-based watermarking methods in AWGN and uniform noise attacking channels. Experimental results of computer simulations demonstrate significant performance enhancement of the designed modified DM and DC-DM watermarking techniques in comparison to the classically elaborated known-host-state schemes in terms of the selected performance measure.
KEYWORDS: Printing, Multimedia, Information security, Visual communications, Information visualization, Visualization, Steganography, Digital watermarking, Electronic imaging, Data processing
In this paper we address visual communications via printing channels from an information-theoretic point of view as communications with side information. The solution to this problem addresses important aspects of multimedia data processing, security and management, since printed documents are still the most common form of visual information representation. Two practical approaches to side information communications for printed documents are analyzed in the paper. The first approach represents a layered joint source-channel coding for printed documents. This approach is based on a self-embedding concept where information is first encoded assuming a Wyner-Ziv set-up and then embedded into the original data using a Gel'fand-Pinsker construction and taking into account properties of printing channels.
The second approach is based on Wyner-Ziv and Berger-Flynn-Gray set-ups and assumes two separated communications channels where an appropriate distributed coding should be elaborated. The first printing channel is considered to be a direct visual channel for images ("analog" channel with degradations). The second "digital channel" with constrained capacity is considered to be an appropriate auxiliary channel. We demonstrate both theoretically and practically how one can benefit from this sort of "distributed paper communications".
In this paper we consider the problem of capacity analysis in the framework of information-theoretic model of data hiding. Capacity is determined by the stochastic model of the host image, by the distortion constraints and by the side information about watermarking channel state available at the encoder and at the decoder. We emphasize the importance of proper modeling of image statistics and outline the possible decrease in the expected fundamental capacity limits, if there is a mismatch between the stochastic image model used in the hider/attacker optimization game and the actual model used by the attacker. To obtain a realistic estimation of pssible embedding rates we propose a novel stochastic non-stationary image model that is based on geometrical priors. This model outperforms the previously analyzed EQ and spike models in reference application such as denoising. Finally, we demonstrate how the proposed model influences the estimation of capacity for real images. We extend our model to different transform domains that include orthogonal, biorthogonal and overcomplete data representations.
An important problem constraining the practical exploitation of robust watermarking technologies is the low robustness of the existing algorithms against geometrical distortions such as rotation, scaling, cropping, translation, change of aspect ratio and shearing. All these attacks can be uniquely described by general affine transforms. In this work, we propose a robust estimation method using apriori known regularity of a set of points. These points can be typically local maxima, or peaks, resulting either from the autocorrelation function (ACF) or from the magnitude spectrum (MS) generated by periodic patterns, which result in regularly aligned and equally spaced points. This structure is kept under any affine transform. The estimation of affine transform parameters is formulated as a robust penalized Maximum Likelihood (ML) problem. We propose an efficient approximation of this problem based on Hough transform (HT) or Radon transform (RT), which are known to be very robust in detecting alignments, even when noise is introduced by misalignments of points, missing points, or extra points. The high efficiency of the method is demonstrated even when severe degradations have occurred, including JPEG compression with a quality factor of 50%, where other known algorithms fail. Results with the Stirmark benchmark confirm the high robustness of the proposed method.
This work advocates the formulation of digital watermarking as a communication problem. We consider watermarking as communication with side information available for both encoder and decoder. A generalized watermarking channel is considered that includes geometrical attacks, fading and additive non-Gaussian noise. The optimal encoding/decoding scenario is discussed for the generalized watermarking channel.
KEYWORDS: Digital watermarking, Video, Video compression, Denoising, Computer programming, Fourier transforms, Gold, Resistance, Information security, Digital filtering
These last years, the rapidly growing digital multimedia market has revealed an urgent need for effective copyright protection mechanisms. Therefore, digital audio, image and video watermarking has recently become a very active area of research, as a solution to this problem. Many important issues have been pointed out, one of them being the robustness to non-intentional and intentional attacks. This paper studies some attacks and proposes countermeasures applied to videos. General attacks are lossy copying/transcoding such as MPEG compression and digital/analog (D/A) conversion, changes of frame-rate, changes of display format, and geometrical distortions. More specific attacks are sequence edition, and statistical attacks such as averaging or collusion. Averaging attack consists of averaging locally consecutive frames to cancel the watermark. This attack works well for schemes which embed random independent marks into frames. In the collusion attack the watermark is estimated from single frames (based on image denoising), and averaged over different scenes for better accuracy. The estimated watermark is then subtracted from each frame. Collusion requires that the same mark is embedded into all frames. The proposed countermeasures first ensures robustness to general attacks by spread spectrum encoding in the frequency domain and by the use of an additional template. Secondly, a Bayesian criterion, evaluating the probability of a correctly decoded watermark, is used for rejection of outliers, and to implement an algorithm against statistical attacks. The idea is to embed randomly chosen marks among a finite set of marks, into subsequences of videos which are long enough to resist averaging attacks, but short enough to avoid collusion attacks. The Bayesian criterion is needed to select the correct mark at the decoding step. Finally, the paper presents experimental results showing the robustness of the proposed method.
KEYWORDS: Digital watermarking, Video, Video compression, Fourier transforms, Image compression, 3D video compression, Information security, Gold, Digital video discs, Digital video recorders
This paper proposes a new approach for digital watermarking and secure copyright protection of videos, the principal aim being to discourage illicit copying and distribution of copyrighted material. The method presented here is based on the discrete Fourier transform (DFT) of three dimensional chunks of video scene, in contrast with previous works on video watermarking where each video frame was marked separately, or where only intra-frame or motion compensation parameters were marked in MPEG compressed videos. Two kinds of information are hidden in the video: a watermark and a template. Both are encoded using an owner key to ensure the system security and are embedded in the 3D DFT magnitude of video chunks. The watermark is a copyright information encoded in the form of a spread spectrum signal. The template is a key based grid and is used to detect and invert the effect of frame-rate changes, aspect-ratio modification and rescaling of frames. The template search and matching is performed in the log-log-log map of the 3D DFT magnitude. The performance of the presented technique is evaluated experimentally and compared with a frame-by-frame 2D DFT watermarking approach.
We address the problem of automatically extracting visual indexes from videos, in order to provide sophisticated access methods to the contents of a video server. We focus on tow tasks, namely the decomposition of a video clip into uniform segments, and the characterization of each shot by camera motion parameters. For the first task we use a Bayesian classification approach to detecting scene cuts by analyzing motion vectors. For the second task a least- squares fitting procedure determines the pan/tilt/zoom camera parameters. In order to guarantee the highest processing speed, all techniques process and analyze directly MPEG-1 motion vectors, without need for video decompression. Experimental results are reported for a database of news video clips.
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