Sharif Digital Repository

During the past two decades, the lattice Boltzmann (LB) method has been introduced as a class of computational fluid dynamic methods for fluid flow simulations. In this method, instead of solving the Navier Stocks equation, the Boltzmann equation is solved to simulate the flow of a fluid. This method was originally developed based on uniform grids. However, in order to model complex geometries such as porous media, it can be very slow in comparison with other techniques such as finite differences and finite elements. To eliminate this limitation, a number of studies have aimed to formulate the lattice Boltzmann on the unstructured grids. This paper deals with simulating fluid flow through a... 

Reducing the time required for MRI, has taken a lot of attention since its inventions. Compressed sensing (CS) is a relatively new method used a lot to reduce the required time. Usage of ordinary compressed sensing in MRI imaging needs conversion of 2D MRI signal (image) to 1D signal by some techniques. This conversion of the signal from 2D to 1D results in heavy computational burden. In this paper, based on separable transforms, a method is proposed which enables the usage of CS in MRI directly in 2D case. By means of this method, imaging can be done faster and with less computational burden  

As an alternative to adaptive nonlinear schemes for dimensionality reduction, linear random projection has recently proved to be a reliable means for high-dimensional data processing. Widespread application of conventional random projection in the context of image analysis is, however, mainly impeded by excessive computational and memory requirements. In this paper, a two-dimensional random projection scheme is considered as a remedy to this problem, and the associated key notion of concentration of measure is closely studied. It is then applied in the contexts of image classification and sparse image reconstruction. Finally, theoretical results are validated within a comprehensive set of... 

A new and efficient dimension reduction method is introduced in this paper. The proposed method, almost the same as the well-known principal component analysis (PCA) method, enjoys the properties of uncorrelatedness of resulting components and orthogonality of transform coefficients. In addition, by incorporating spatial and spectral properties among image pixels, the method obtains more accurate classification results with less computational cost  

Background: In nuclear medicine application often it is required to use computational methods for evaluation of organ absorbed dose. Monte Carlo simulation and phantoms have been used in many works before. The shape, size and volume in organs are varied, and this variation will produce error in dose calculation if no correction is applied. Materials and Methods: A computational framework for constructing individual phantom for dosimetry was performed on five liver CT scan data sets of Japanese normal individuals. The Zubal phantom was used as an original phantom to be adjusted by each individual data set. This registration was done by Spherical Harmonics (SH) and Thin-Plate Spline methods.... 

Compressed Sensing (CS), as a new rapidly growing research field, promises to effectively recover a sparse signal at the rate of below Nyquist rate. This revolutionary technology strongly relies on the sparsity of the signal and incoherency between sensing basis and representation basis. Exact recovery of a sparse signal will be occurred in a situation that the signal of interest sensed randomly and the measurements are also taken based on sparsity level and log factor of the signal dimension. In this paper, compressed sensing method is proposed to reduce the noise and reconstruct the image signal. Noise reduction and image reconstruction are formulated in the theoretical framework of... 

In soccer matches, 3D reconstruction is a main part of many applications including free-viewpoint broadcasting, match analysis, augmented reality, and refereeing examination. The main challenge of 3D reconstruction in soccer scenes is the human body reconstruction. Although 3D reconstruction methods have been improved to a high extent in controlled condition, still there are lots of uncovered issues in outdoor scene reconstructions with uncontrolled conditions. In this paper, a view-dependent depth optimization method is presented which addresses two of these issues in soccer scenes. These issues include inaccurate camera calibrations and limited number of input cameras. This method will... 

This paper presents the results of a vulnerability assessment of the damaged Al-Askari shrine located in Samarra, Iraq by finite element analysis. Reliable material characteristics are derived using limited experimental data on this historical building in order to be utilized in the numerical models. It is concluded that the cracked piers are not vulnerable under the weight of the newly added dome. However, the cracks in the piers widen under design seismic loads, which results in unbalanced settlements in the piers and torsional cracks in the dome. The vulnerability of the minarets is more severe, necessitating heavy reinforcement at their bases and adequate anchorage to the masonry... 

The Al-Askari shrine, located in Samarra, Iraq, is a remarkable example of a building with ancient Islamic architecture and construction that was heavily damaged by massive bombings. The bombings were carried out by two separate terrorist attacks in 2006 and 2007. This paper summarizes the important undertakings in the identification of shrine buildings in terms of structural and architectural background and characteristics, damage classification and monitoring, site conditions and material properties. Moreover, the shortcomings of a series of previously performed partial restorations are elaborated upon. The results and findings of this study can be utilized as database in other numerical... 

A new and efficient method for incorporating the spatiality into difference-based change detection (CD) algorithms is introduced in this paper. It uses the spatial derivatives of image pixels to extract spatial relations among them. Based on this methodology, the performances of two famous difference-based CD methods, conventional polynomial regression (CPR) and multivariate alteration detection (MAD), are improved and called modified polynomial regression (MPR) and spatial multivariate alteration detection (SMAD), respectively. Various quantitative and qualitative evaluations have shown the superiority of MPR over CPR and SMAD over MAD. Also, the superiority of SMAD over all mentioned CD... 

Gonbad-e Qabus, with a height of 52.8 m that makes it the tallest pure-brick tower in the world, located in the northern part of Iran, represents one of the most magnificent structures of the early Islamic centuries. This structure is still standing among the chaos of urban life and construction, catching the eyes of beholders even from far distances. This paper summarizes the historical and architectural background of this monumental structure and the important restorations carried out mainly in the past century. Various types of existing and potential structural and architectural damages are classified and elaborated in detail, and for each problem, a series of proposed solutions are... 

This paper investigates the problem of recovering missing samples using methods based on sparse representation adapted for visually enhanced quality of reconstruction of image signals. Although, the popular Mean Square Error (MSE) criterion is convex and simple, it may not be entirely consistent with Human Visual System (HVS). Thus, instead of ℓ2-norm or MSE, a new perceptual quality measure is used as the similarity criterion between the original and the reconstructed images. The proposed criterion called Convex SIMilarity (CSIM) index is a modified version of the Structural SIMilarity (SSIM) index, which despite its predecessor, is convex and uni-modal. We derive mathematical properties... 

This brief introduces a modified backprojection algorithm to compensate the effect of redundancy of captured data in spatial-fourier or k-space domain for multi-static millimeter-wave imaging. The data measured by each transmitter-receiver pair is explained in k-space domain and the redundancies are determined. Such redundancies act as an undesirable filter that distorts the appearance of the resulting image. Our goal is to modify SAR backprojection algorithm to address this problem, where extensive simulation and experimental results are also provided. Our measurements show a significant improvement in the overall quality and edge preservation in the reconstructed image of objects under the... 

In this paper, a new approach toward material detection and classification, based on the spectral analysis of millimeter-wave images, using machine learning technique is proposed. The focus of this paper is to detect concealed dangerous materials. It is shown that by using adequate number of training data captured from different materials of interest, the trained machine could detect concealed dangerous materials with an acceptable accuracy. The training phase is performed with materials of varying thickness, shape, background, covering layers and distance. The training data is collected with laboratory experiments in the frequency range of 27-31 GHz with 51 frequency samples. The results... 

In this paper, we propose an algorithm for recovery of sparse and low-rank components of matrices using an iterative method with adaptive thresholding. In each iteration of the algorithm, the low-rank and sparse components are obtained using a thresholding operator. The proposed algorithm is fast and can be implemented easily. We compare it with the state-of-the-art algorithms. We also apply it to some applications such as background modeling in video sequences, removing shadows and specularities from face images, and image restoration. The simulation results show that the proposed algorithm has a suitable performance with low run-time. © 2017 Elsevier Inc  

Rapidly improving video-editing software tools and algorithms have made video content manipulation and modification feasible even by inexpert users. Detecting video tampering and recovering the original content of the tampered videos is, thus, a major need in many applications. Although detection and localization of the tampering in certain types of video editing have successfully been addressed in the literature, attempts for recovering the tampered videos are bound to methods using watermarks. In this paper, a scheme for the reconstruction of the tampered video through watermarking is proposed. The watermark payload, which consists of highly compressed versions of keyframes of the video... 

This paper focuses on an efficient approach for designing multi-static arrays for millimeter-wave imaging, based on the k -space or Fourier-spatial domain characteristic of imaging systems. Our goal is to decrease the redundancy of the data measured by each antenna and to improve the resolution of the reconstructed image. The proposed technique is based on determining the role of each transmitter and receiver, in collecting the data from each voxel of the target in k -space domain and then rotating the transmitters' beams to measure the desirable information. The effect of non-uniform redundant k -space domain frequency samples that act as an undesirable filter is compensated using a... 

With the dominance of digital imaging systems, we are often dealing with discrete-domain samples of an analog image. Due to physical limitations, all imaging devices apply a blurring kernel on the input image before taking samples to form the output pixels. In this paper, we focus on the reconstruction of binary shape images from few blurred samples. This problem has applications in medical imaging, shape processing, and image segmentation. Our method relies on representing the analog shape image in a discrete grid much finer than the sampling grid. We formulate the problem as the recovery of a rank $r$ matrix that is formed by a Hankel structure on the pixels. We further propose efficient... 

In this brief, an imaging methodology for mono-static millimeter-wave systems is introduced. When the measured object hologram is piece-wise smooth with sharp boundaries, both low-pass and high-pass components are present in a transform domain. Nevertheless, the edges are sparse in transform domain with respect to the image dimensions. It is shown that the down-sampling of the hologram with an appropriate rate determined by the sparsity level, includes the adequate information of all components for image reconstruction. Using random samples, an algorithm is proposed to recover all the sparse components, iteratively. Simulation results illustrate that a high-resolution recovery can be...