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Background modeling is commonly used in image processing applications. Stationary camera assumption, the basic assumption of background modeling, becomes invalid in some cases such as movement of camera, movement of platform on which the camera is mounted, oscillation of camera due to wind etc. The purpose of this study is to keep providing the background information while the view point of the camera...
In this work, an algorithm is introduced that classifies test images into their originated countries using composite faces generated according to different countries. Also aim to increase success rate at implementation process using three color channel (R-G-B), color feature vector and local standard deviation matrix. Algorithm used Kernel Principal Component Analysis with gauss kernel structure for...
Visual tracking has an important place among computer vision applications. Visual tracking with particle filters is a well-known methodology. The performance of particle filters is dependent on efficient sampling of the state space, which in turn, is dependent on number of particles. In this paper, Rao-Blackwell technique is applied to particle filters to improve sampling efficiency. Both algorithms...
In this paper, by introducing a new packing strategy in the 3rd stage of the standard OBBP frame packing algorithm a substantial improvement in frame utilization and hence packing efficiency has been attained. Firstly, the efficiency of the Modified OBBP (MOBBP) and standard OBBP algorithms were obtained through simulations where a subframe with a capacity of 840 slots (60 subchannels × 28 symbols)...
OFDMA-based mobile relay enhanced cellular networks which have lower infrastructure cost and larger coverage areas are important technologies for the next generation communication systems since they allow to communicate at higher data rates. However, it is required to develop efficient radio resource management algorithms in order to reveal these advantages. Thus, in this study, relay selection and...
The recently proposed function controlled variable step-size least-mean-square (FCVSSLMS) algorithm has shown high performance. The performance of the algorithm can be improved further if the system is sparse. In this paper, we propose a new algorithm based on algorithm. The proposed algorithm imposes an approximate l0-norm penalty in the cost function of the FCVSSLMS algorithm. The performance of...
Lorentzian space is used in Mathematics and Physics. This space has also potential applications in pattern recognition because of its special characteristics. Lorentz space has different characteristics and different inner product definition than Euclidean space; therefore distances between points are calculated in a different way. In this study, contribution of this space to the classification problem...
Electronic Support Measures (ESM) system is an important function of electronic warfare which provides the real time projection of radar activities. Such systems may encounter with very high density pulse sequences and it is the main task of an ESM system to deinterleave these mixed pulse trains with high accuracy and minimum computation time. These systems heavily depend on time of arrival analysis...
Modeling of user behaviour becomes almost a necessity on data networks nowadays. Besides using their resources more efficiently, many data communication systems will perform more effective via estimation of statistical distribution of packet counts transferred (uploaded or downloaded) by users at once. Hence, the purpose of this study is to search suitable statistical models for distribution of packet...
The spectral matching, statistical and kernel based methods are the most widely known classification algorithms for hyperspectral imaging. Spectral matching algorithms try to identify the similarity of the unknown spectral signature of test pixels with the expected signature. In this study, an efficient spectral similarity method employing Multi-Scale Vector Tunnel Algorithm (MS-VTA) for supervised...
In this study, it is aimed to follow a visual route by an Unmanned Aerial Vehicle (UAV). The recognition of the predetermined line by using image processing algorithms and the process of following the route by using the method of Tangent Vector Field Guidance (TVFG) have been performed in indoor and outdoor experiments. UAV s following the correct route has been ensured by calculating the deflection...
In this studyareal time skeletonization system is implemented on FPGA. Skeletonization forms the backbone of many tracking and matching applications in image processing. The computational complexity of the skeletonization algorithms highly increases to reach a performance close to perfect skeleton. This complexity makes it impossible for the systems to cope with real time requirements. Thus, in this...
In this paper, an algorithm which is implemented for cancer detection in image processing and the results of the algorithm are mentioned. Researched work has three main steps. In first step, images are passed through significant steps for noise removal; at the second step, various histogram thresholds are calculated and at the last step cancer is detected with respect to calculated thresholds. As...
Underwater acoustic vector sensors (AVS) are devices which can measure scalar pressure and three dimensional acceleration or particle velocity with only one sensor. Bearing estimation for the target can be accomplished by these four measured scalar values. Algorithms based on closed-form expressions or beamforming can be carried out for direction finding by using the axial projections of the gradient...
Multiple image thresholding is a popular method used to separate homogeneous subsets of gray level images. To find the optimum threshold in the image in the literature is still a research topic. Many image thresholding method uses the histogram of the image. In this study, the objective function of Otsu method which is a statistical process, Particle Swarm Optimization with an intuitive algorithm...
In this paper, we consider the linear estimation problem under structured data uncertainties. A robust algorithm is presented under bounded uncertainties under the mean square error (MSE) criterion. The performance of the linear estimator is defined relative to the performance of the linear minimum MSE (MMSE) estimator tuned to the underlying unknown data uncertainties, i.e., the introduced algorithm...
A new deconvolution algorithm based on making orthogonal projections onto the epigraph set of a convex cost function is presented. In this algorithm, the dimension of the minimization problem is lifted by one and sets corresponding to the cost function and observations are defined. If the utilized cost function is convex in RN, the corresponding epigraph set is also convex in RN+1. The deconvolution...
One Time Password which is fixed length strings to perform authentication in electronic media is used as a one-time. In this paper, One Time Password production methods which based on hash functions were investigated. Keccak digest algorithm was used for the production of One Time Password. This algorithm has been selected as the latest standards for hash algorithm in October 2012 by National Instute...
In this paper, we propose robust set-membership filtering algorithms against impulsive noise. Firstly, we introduce set-membership normalized least absolute difference algorithm (SM-NLAD). This algorithm provides robustness against impulsive noise through pricing the absolute error instead of the square. Then, in order to achieve comparable convergence performance in the impulse-free noise environments,...
This study proposes an improved Multi-Dimensional Hough Transform technique for the detection of low SNR targets (dim targets) in radar data. The proposed Track-Before-Detect technique improves the Multi-Dimensional Hough Transform by limiting the target's maximum velocity and incorporating the SNR values of the targets in the algorithm. In addition, the performance is enhanced by confirming the Hough...
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