Sharif Digital Repository

This paper presents a new transform domain to evaluate the goodness of fit of natural image data to the common Benford's Law. The evaluation is made by three statistical fitness criteria including Pearson's chi-square test statistic, normalized cross correlation and a distance measure based on symmetrized Kullback-Leibler divergence. It is shown that the serial combination of variance filtering and block 2-D discrete cosine transform reveals the best goodness of fit for the first significant digit. We also show that the proposed transform domain brings reasonable fit for the second, third and fourth significant digits. As an application, the proposed transform domain is utilized to detect... 

The growth of data communication networks has made digital watermarking an important issue for copyright and content protection. Achieving high level of robustness and good transparency are the main objectives of developing every digital watermarking algorithm. From among transform domains as the basis of watermark hiding place, Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) are the most commonly used transforms in literature. In this paper we propose a new hybrid DWT-SVD domain watermarking scheme taking into account the energy content of every chosen block of the selected DWT sub-band coefficients. Before embedding, we append a... 

In this paper, a discrete cosine transform (DCT) based blind watermarking scheme based on spread spectrum communications is proposed. We perform block-based DCT (BDCT) on the host image; then using the DC coefficients of each block, we construct a low-resolution approximation image. We apply BDCT on this approximation image, then watermark is embedded by adding a pseudo random noise sequence into its high frequencies. In detection stage, we extract the approximation image from the watermarked image, then the same pseudo random noise sequence is generated, and its correlation is computed with high frequencies of the watermarked approximation image. In our method, higher robustness is obtained... 

In this paper we present a blind low frequency watermarking scheme on gray level images, which is based on DCT transform and spread spectrum communications technique. We compute the DCT of non overlapping 8x8 blocks of the host image, then using the DC coefficients of each block we construct a low-resolution approximation image. We apply block based DCT on this approximation image, then a pseudo random noise sequence is added into its high frequencies. For detection, we extract the approximation image from the watermarked image, then the same pseudo random noise sequence is generated, and its correlation is computed with high frequencies of the watermarked approximation image. In our method,... 

In this paper, a DCT-based blind watermarking scheme based on spread spectrum communications is proposed. We perform block-based DCT on the host image; then using the DC coefficients of each block, we construct a low-resolution approximation image. We apply block-based DCT on this approximation image, then watermark is embedded by adding a pseudo random noise sequence into its high frequencies. In detection stage, we extract the approximation image from the watermarked image, then the same pseudo random noise sequence is generated, and its correlation is computed with high frequencies of the watermarked approximation image. In our method, higher robustness is obtained because of embedding... 

Watermarking is a way that is used to protect the copyright of images. As the existing watermarking methods are not robust enough a new novel scheme is needed. In this paper, we propose a zero-watermark discrete cosine transformation-based copyright protection scheme, in which a normalization procedure is applied in both watermark embedding and extraction to make our scheme more robust to geometric distortions. This method is resistant to malicious signal processing and geometric attacks such as blurring, JPEG compression, noise adding, sharpening, scaling, rotation and cropping. Experimental results on images with different complexity show that our proposed scheme outperforms related... 

Mostly the embedding capacity of steganography methods is assessed in non-zero DCT coefficients. Due to unequal distribution of non-zero DCT coefficients in images with different contents, images with the same number of non-zero DCT coefficients may have different actual embedding capacities. This paper introduces embedding capacity as a property of images in the presence of multiple steganalyzers, and discusses a method for computing embedding capacity of cover images. Using the capacity constraint, embedding can be done more secure than the state when the embedder does not know how much data can be hidden securely in an image. In our proposed approach, an ensemble system that uses... 

This paper presents a robust model predictive control algorithm with a time-varying terminal constraint set for systems with model uncertainty and input constraints. In this algorithm, the nonlinear system is approximated by a linear model where the approximation error is considered as an unstructured uncertainty that can be represented by a Lipschitz nonlinear function. A continuum of terminal constraint sets is constructed off-line, and robust stability is achieved on-line by using a variable control horizon. This approach significantly reduces the computational complexity. The proposed robust model predictive controller with a terminal constraint set is used in tracking set-points for... 

In this paper, an algorithm for image coding based on a sparse 3-dimensional Discrete Cosine Transform (3D DCT) is studied. The algorithm is essentially a method for achieving a sufficiently sparse representation using 3D DCT. The experimental results obtained by the algorithm are compared to the 2D DCT (used in JPEG standard) and wavelet db9/7 (used in JPEG2000 standard). It is experimentally shown that the algorithm, that only uses DCT but in 3 dimensions, outperforms the DCT used in JPEG standard and achieves comparable results (but still less than) the wavelet transform. © Springer-Verlag Berlin Heidelberg 2009  

The three dimensional discrete cosine transform (3D DCT) has been widely used in many applications such as video compression. On the other hand, the kary n-cube is one of the most popular interconnection networks used in many recent multicomputers. As direct calculation of 3D DCT is very time consuming, many researchers have been working on developing algorithms and special-purpose architectures for fast computation of 3D DCT. This paper proposes a parallel algorithm for efficient calculation of 3D DCT on the k-ary n-cube multicomputers. The time complexity of the proposed algorithm is of O(N) for an N × N × N input data cube while direct calculation of 3D DCT has a complexity of O(N6). ©... 

This paper focuses on the effect of deep cryogenic treatment (-196 °C) on microstructure and mechanical properties of AZ91 magnesium alloy. The execution of deep cryogenic treatment on samples changed the distribution of β precipitates. The tiny laminar β particles almost dissolved in the microstructure and the coarse divorced eutectic β phase penetrated into the matrix. This microstructural modification resulted in a significant improvement on mechanical properties of the alloy. The steady state creep rates were measured and it was found that the creep behavior of the alloy, which is dependent on the stability of the near grain boundary microstructure, was improved by the deep cryogenic... 

Multiple description coding (MDC) is a technique where multiple streams from a source video are generated, each individually decodable and mutually refinable. MDC is a promising solution to overcome packet loss in video transmission over noisy channels, particularly for real-time applications in which retransmission of lost information is not practical. A problem with conventional MDC is that the achieved side distortion quality is considerably lower than single description coding (SDC) quality except at high redundancies which in turn leads to central quality degradation. In this paper, a new mixed layer MDC scheme is presented with no degradation in central quality, and providing better... 

The main concern of steganography (image hiding) methods is to embed a secret image into a host image in such a way that it causes minimum distortion to the host; to make it possible to extract a version of secret image from the host in such a way that the extracted version of secret image be as similar as possible to its original version (this should be possible even after usual attacks on the host image), and to provide ways of embedding secret images with larger size into a given host image. In this paper we propose a method that covers all above mentioned concerns by suggesting the idea of finding from an image data base, the most suitable host for a given secret image. In our method,... 

We propose a blind image steganalysis method based on the Singular Value Decomposition (SVD) of the Discrete Cosine Transform (DCT) coefficients that are revisited in this work. We compute geometric mean, mean of log values, and statistical moments (mean, variance and skewness) of the SVDs of the DCT sub-blocks that are averaged over the whole image to construct a 480-element feature vector for steganalysis. These features are fed to a Support Vector Machine (SVM) classifier to discriminate between stego and cover images. Experimental results show that the proposed method outperforms most powerful steganalyzers when applied to some well-known steganography algorithms