Sharif Digital Repository

A new method for digital video watermarking is presented in this paper. For data embedding we use 3-D ridgelet domain introduced by Helbert. The redundancy of this transform is substantial, so extraction of the hidden data is impossible in this domain. To overcome this problem, we introduce a modified ridgelet transform with little redundancy, and embed watermark in this domain. Experimental results show that this scheme is robust against collusion attack, frame cropping, frame swapping, frame dropping, noise attack and the MJPEG (Motion JPEG) compression  

Video activity analysis is used in various video applications such as human action recognition, video retrieval, video archiving. In this paper, we propose to apply 3D wavelet transform statistics to natural video signals and employ the resulting statistical attributes for video modeling and analysis. From the 3D wavelet transform, we investigate the marginal and joint statistics as well as the Mutual Information (MI) estimates. We show that marginal histograms are approximated quite well by Generalized Gaussian Density (GGD) functions; and the MI between coefficients decreases when the activity level increases in videos. Joint statistics attributes are applied to scene activity grouping,... 

This paper addresses a new approach to the keyframe extraction problem employing generalized Gaussian density (GGD) parameters of wavelet transform subbands along with Kullback-Leibler distance (KLD) measurement. Shot and cluster boundaries are selected using KLDs between GGD feature vectors, and then keyframes are located based on similarity and dissimilarity criteria. Objective and subjective evaluations show the high accuracy of this new approach compared with traditional methods  

In this paper, we present a spatio-temporal event-based approach to video signal analysis and abstraction employing wavelet transform features. The video signal is assumed to be a sequence of overlapping independent visual components called events, which typically are temporally overlapping compact functions that describe temporal evolution of a given set of the spatial parameters of the video signal. We utilize event-based temporal decomposition technique to resolve the overlapping arrangement of the video signal that is known to be one of the main concerns in video analysis via conventional frame-based schemes. In our method, a set of spatial parameters, extracted from the video, is... 

We present an Autoregressive (AR) modeling method for video signal analysis based on 2D Wavelet Statistics. The video signal is assumed to be a combination of spatial feature time series that are temporally approximated by the AR model. The AR model yields a linear approximation to the temporal evolution of a stationary stochastic process. Generalized Gaussian Density (GGD) parameters, extracted from 2D wavelet transform subbands, are used as the spatial features. Wavelet transform efficiently resembles the Human Visual System (HVS) characteristics and captures more suitable features, as compared to color histogram features. The AR model describes each spatial feature vector as a linear... 

We propose an event based approach for locating keyframes in natural video through detection of locally correlated spectral targets. Temporal Decomposition (TD) is used to describe a set of spectral parameters of the video as a linear combination of a set of temporally overlapping event functions. This process provides preliminary information about keyframes, by selecting the frames located at event centroids as the keyframe candidates. No shot or shot cluster boundary detection is needed and keyframes are extracted directly from among event centroids that are much smaller in number than the number of frames. Generalized Gaussian Density (GGD) parameters, extracted from 2D wavelet transform... 

A robust fingerprint recognition system based on marginal statistics of 2D wavelet transform is introduced which significantly improves the accuracy of previous wavelet based approaches due to 1) a better selection of features extracted from the wavelet transform, and 2) a more accurate distance measure to find the similarity between fingerprints. A combination of Jain and Poincare algorithms is employed to locate the fingerprint reference point. The main part of the fingerprint image is chosen as a rectangle with the reference point at its center. The image is then divided into nonoverlapping sub-images, the wavelet transform is applied to the bi-level sub-images, and Generalized Gaussian... 

In this paper, Kullback-Leibler Distance (KLD) is employed to measure the dissimilarity between marginal statistical features of contourlet transform to fingerprint identification. Conourlet transform is a non separable two dimensional transform which can well capture the geometry of edges in the images which convey important information for the human visual system (HVS). Here, marginal statistics of each transform subband are modeled by a Generalized Gaussian Density (GGD) model and the GGD parameters-α and β- are granted as the extracted features from the corresponding subbands and the fingerprint recognition is done based on k-NN classifier employing Kullback-Leibler Distance (KLD)... 

This paper presents an event based scheme for uncompressed video watermarking. The video signal is assumed to be a sequence of overlapping visual components - called events. We address this overlapping structure of video contents and present an event based approach through employing a block based Temporal Decomposition (TD) scheme. The TD describes a set of spectral parameters of the video as a linear combination of a set of temporally overlapping compact event functions. We have applied the decomposition results to digital video watermarking. To construct the matrix of parameters in the TD, Multiresolution Singular Value Decomposition (MR-SVD) is utilized and singular values of a set of... 

Segmentation is a very important stage of Farsi/Arabie character recognition systems. A new segmentation algorithm -for multi font Farsi/Arabic texts- based on the conditional labeling of the up contour and down contour is presented. A pre-processing technique is used to adjust the local base line for each subword. This algorithm uses adaptive base line for each subword to improve the segmentation results. This segmentation algorithm, in addition to up and down contours, takes advantage of their curvatures also. The algorithm was tested on a data set of printed Farsi texts, containing 22236 characters, in 18 different fonts. 97% of characters were correctly segmented. © 2005 IEEE  

A video activity analysis is presented based on 3D wavelet transform. Marginal and joint statistics as well as mutual information estimates are extracted. Marginal histograms are approximated by Generalized Gaussian Density (GGD) functions. The mutual information between coefficients -as a quantitative estimate of joint statistics- decreases when the activity in the video increases. The relationship between kurtosis graphs, extracted from joint distributions and video activity, is deduced. Results show that the type of activity in the video can be figured out from Kurtosis curves. The GGD and the Kullback-Leibler distance (KLD) are used to retrieve and locate 96% of videos properly  

Using multiple antennas at the transmit and receive sides of a passive radar brings both the benefits of MIMO radar and passive radar. However one of the obstacles arisen in such configuration is the receive antennas placement in proper positions so that the radar performance is improved. Here we just consider the case of positioning one receiver among multiple illuminators of opportunity. Indeed it is a start for the solution of optimizing the geometry of the multiple receivers in a passive radar  

SbCl3 supported on montmorillonite K-10 is an efficient catalyst for the ring opening of epoxides with aromatic amines under solvent-free conditions and microwave irradiation to give the corresponding b-amino alcohols in high yields with high regioselectivity  

In this paper, we consider an integrated sensing and communication (ISAC) system with wireless power transfer (WPT) where an unmanned aerial vehicle (UAV)-based radar serves a group of energy-limited communication users in addition to its sensing functionality. In this architecture, the radar senses the environment in phase 1 (namely sensing phase) and mean-while, the communications users (nodes) harvest and store the energy from the radar transmit signal. The stored energy is then used for information transmission from the nodes to UAV in phase 2, i.e., uplink phase. Performance of the radar system depends on the transmit signal as well as the receive filter; the energy of the transmit... 

One of the important obstacles in MIMO (Multiple Input Multiple Output) radars is the issue of designing proper transmit signals. Indeed, the capability of signal design is a significant advantage in MIMO radars, through which, the system can achieve much better performance. Many different aspects of this performance improvement have been considered yet, and the transmit signals have been designed to attain such goal, e.g., getting higher SNR or better detector's performance at the receiver. However, an important tool for evaluating the radar's performance is its ambiguity function. In this paper, we consider the problem of transmit signal design, in order to optimize the ambiguity function... 

Two gains play key roles in recently developed MIMO wireless communication systems: "spatial diversity" gain and "spatial multiplexing" gain. The diversity gain refers to the capability to decrease the error rate of the MIMO channel, while the multiplexing gain implicitly refers to the amount of increase in the capacity of the MIMO channel. It has been shown that there is a fundamental tradeoff between these two types of gains, meaning interplay between increasing reliability (via an increase in the diversity gain) and increasing data rate (via an increase in the multiplexing gain). On the other hand, recently, MIMO radars have attracted much attention for their superior ability to enhance... 

It is a well known fact that using multiple antennas at transmit and receive sides improves the detection performance. However, in such multiple-input multiple-output (MIMO) configuration, proper positioning of transmitters and receivers is a big challenge that can have significant influence on the performance of the overall system. In addition, determining the power of each transmitter under a total power constraint is a problem that should be solved in order to enhance the performance and coverage of such a system. In this paper, we design the Neyman-Pearson detector under the Rayleigh scatter model and use it to introduce a criterion for the antenna placement at both transmit and receive... 

There has been much interest, recently, towards exploiting the Multiple-Input Multiple-Output (MIMO) technique in radar. It is shown that using multiple antennas at transmit and receive sides can improve the performance of the system. However, in order to analyze the system's performance, its ambiguity function, i.e. the ambiguity function of a MIMO radar, is needed to be defined. In this paper, beginning from the information theoretic definitions, we derive such function, specifically for a MIMO radar with widely separated antennas  

By combining the two ideas of MIMO (Multiple Input Multiple Output) and PCL (Passive Coherent Location) in radar, one can achieve the advantages of both recently developed techniques simultaneously. While using multiple antennas at the receive side provides a spatial diversity of the object to be detected, using multiple illuminators of opportunity, most importantly, makes the radar covert to the interceptors. One obstacle in such MIMO configuration is choosing the positions of the receive antennas. In this paper, after analyzing the Neyman-Pearson detector for the DVB-T based PCL, we introduce the probability of missed detection as a criterion to place the receive antenna. Here, we only...