International Journal of Image, Graphics and Signal Processing @ijigsp
Статьи журнала - International Journal of Image, Graphics and Signal Processing
Все статьи: 1146
Occluded Human Tracking and Identification Using Image Annotation
Статья научная
The important task of human tracking can be difficult to implement in real world environment as the videos can involve complex scenes, severe occlusion and even moving background. Tracking individual objects in a cluttered scene is an important aspect of surveillance. In addition, the systems should also avoid misclassification which can lead to inaccurate tracking. This paper makes use of an efficient image annotation for human tracking. According to the literature survey, this is the first paper which proposes the application of the image annotation algorithm towards human tracking. The method divides the video scene into multiple layers assigning each layer to the individual object of interest. Since each layer has been assigned to a specific object in the video sequence: (i) we can track and analyse the movement of each object individually (ii) The method is able to reframe from misclassification as each object has been assigned a respective layer. The error incurred by the system with movement from one frame to another is presented with detailed simulations and is compared with the conventional Horn–Schunck alone.
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On Calculation of Fractal Dimension of Color Images
Статья научная
Fractal Dimension is a basic parameter of fractal geometry and it has been applied in many fields of application including image analysis, texture segmentation, and shape classification. Many fractal dimensions methods have been evolved depending upon different types of images that could be differentiated with greater precision. In this paper, we propose a color approach based on the modified differential box-counting method to estimate fractal dimension of color images in terms of its smoothness. Here we have experimented on four sets of color images like; sixteen number of real natural texture images, eight sets of controlled experimental fabric images with varied color and texture, twelve numbers of generated synthetic images and four smoothed images of known fractal dimension. The results demonstrated that the said proposed method shows accurate fractal dimension estimation of color texture image and also it indicates FD as 2 for smoothed images, which has already been developed in last decade and indicates higher roughness in color images, to check the accuracy of our proposed method, we used a set of twelve synthetic generated images.
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On the Role of Overlapping Factor in FBMC-SMT Systems
Статья научная
The overlapping factor has a vital role in determining the optimum bandwidth utilization and the desired side band suppression. In this paper, we review one of the filter bank multicarrier technique-staggered multi tone modulation, discuss its efficient implementation in polyphase form and compare between several performance parameters of the same. We also discuss the role of overlapping factor in staggered multi tone modulation systems. We describe a low complexity procedure for generation of the required overlapping factors based on frequency sampling method. Our simulations describe the effectiveness of the optimum value selection for overlapping factor in a staggered multi tone modulation system. The proposed system is theoretically found to be compatible with the Long Term Evolution standards. The performance evaluation of the proposed system in ideal conditions emphasizes about the reduction in spectrum leakage in sidebands of the staggered multi tone modulation system, along with a little increase in system complexity.
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On the Signal-Image Intensity-Curvature Content
Статья научная
The biomedical engineering problem addressed in this work is the one of finding a novel signal-image content measure called intensity-curvature functional making use of all of the second order derivatives of the model function fitted to the data. Given a signal-image made of a sequel of discrete samples and given a model function which embeds the property of second order differentiability, it is possible to quantify the content of the signal-image through a novel approach based on both of the intensity and of the total curvature of the signal-image. The signal-image is fitted with the model function. The total curvature can be calculated through the sum of all of the second order derivatives of the Hessian of the model function fitted to the data. The intensity-curvature functional is defined as the ratio between: (i) the integral of the multiplication between the value of the signal modeled through an interpolation function and the total curvature of the signal-image; both of them at the temporal-spatial location of its sampling (the grid nodes) and, (ii) the integral of the value of the multiplication between the signal modeled through an interpolation function and the total curvature of the signal-image; both of them at any given temporal-spatial location of its re-sampling (intra-pixel location). This manuscript shows both of the formulae and the qualitative results of: the intensity-curvature functional and the intensity-curvature measures which are conceptually linked to the intensity-curvature functional. The formulations here presented make the engineering innovation. The intensity-curvature functional depends on both of the model function fitting the signal-image and the magnitude of re-sampling employed to calculate the second order derivatives of the Hessian of the model function.
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Статья научная
In this paper, we propose a robust environmental sound spectrogram classification approach. Its purpose is surveillance and security applications based on the reassignment method and log-Gabor filters. Besides, the reassignment method is applied to the spectrogram to improve the readability of the time-frequency representation, and to assure a better localization of the signal components. Our approach includes three methods. In the first two methods, the reassigned spectrograms are passed through appropriate log-Gabor filter banks and the outputs are averaged and underwent an optimal feature selection procedure based on a mutual information criterion. The third method uses the same steps but applied only to three patches extracted from each reassigned spectrogram. The proposed approach is tested on a large database consists of 1000 sounds belonging to ten classes. The recognition is based on Multiclass Support Vector Machines.
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Online trial room based on human body shape detection
Статья научная
High returning rate of garments products have become a notable problem for online fashion shopping. This problem is partially caused by using different standards for measuring cloth sizes on different websites. In this research, we have designed a set of equipment to capture images of t-shirts of any color and propose an automatic cloth measurement approach using image processing techniques. A method has been introduced to recognize feature points, which has been used to calculate the cloth sizes. The method has provided a useful and efficient tool for cloth measurement. The photographs have been taken in a controlled environment, and then clothes have been categorized with the proportions of the neck, shoulder, chest width, upper waist, lower waist, and length. In this method, we have measured the t-shirt size for men by calculating the chest width and length of men. For this, a dataset has been created in a specific environment. This method has integrated with a web-based application. We have validated our work by calculating RMSE values.
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Статья научная
Failure modeling is an essential component of reliability engineering. Enhanced failure rate modeling techniques are vital to the effective development of predictive and analytical methodologies, demonstration of the engineering procedure, allocation of procedures, design, and control of procedures. However, failure rate modeling has not been given adequate treatment in the literature. The need to investigate failure rate modeling leveraging cutting-edge techniques cannot be overemphasized. This paper proposed and applied a joint support vector regression (SVR) and wavelet transform (WT) approach termed (WT-SVR) to training and learning the call failures rate in wireless system networks. The wavelet transform has been accomplished using the wavelet compression sensing technique. In this technique, the standardized call failure rate data first go through a wavelet filtering transformation matrix. This is followed by separating and outputting the transformed filtered components in the compression phase. Finally, the transformed filtered output components were trained and evaluated using the SVR based on statistical learning theory. The resultant outcome revealed that the proposed WT-SVR learning method is by far better than using only the SVR method for call rate prognostic analysis. As a case in point, the WT-SVR attained STD values of 0.12, 0.21, 2.32, 0.22, 0.90, 0.81 and 0.34 on call failure data estimation compared to the basic SVR that attained higher STD values of 0.45, 0.98, 0.99, 0.46, 1.44, 2.32 and 3.22, respectively.
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Статья научная
This paper applies a neural-network-based approximate dynamic programming (ADP) method, namely, the action dependent heuristic dynamic programming (ADHDP), to an industrial sucrose crystallization optimal control problem. The industrial sucrose crystallization is a nonlinear and slow time-varying process. It is quite difficult to establish a precise mechanism model of the crystallization, because of complex internal mechanism and interacting variables. We developed a neural network model of the crystallization based on the data from the actual sugar boiling process of sugar refinery. The ADHDP is a learningand approximation-based approach which can solve the optimization control problem of nonlinear system. The paper covers the basic principle of this learning scheme and the design of neural network controller based on the approach. The result of simulation shows the controller based on action dependent heuristic dynamic programming approach can optimize industrial sucrose crystallization.
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Статья научная
In this paper, the Series-Parallel (SP) and Total-Cross-Tied (T-C-T) type of conventional solar photovoltaic (SPV) array configurations or topologies are considered for modeling and comparative analysis and the parameters mainly maximum power of array, shading losses, number of interconnections or ties between array SPV modules are compared with the proposed optimal configuration under six partial shading scenarios and one un shaded case. The proposed optimal topology, optimize the number of ties required among PV modules and improves the output power of SPV array as compare to TCT configuration and also minimizes the shading power losses. These optimal interconnections are based on the location of number of shaded modules in the SPV Array. For this study, the Vikram Solar ELDORA 270 PV modules are used for modeling and simulation of SP, TCT and proposed optimal topologies in MATLAB/ Simulink software.
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Optimization in image fusion using genetic algorithm
Статья научная
Day by day, the advancement in sensor technology is increasing which is used for image acquisition. Different sensors can acquire the information of different wavelength. These sensors are not able to capture the complete information from the scene. Thus it is necessary to combine the images from different sensors to produce more informative image. Image fusion is the process of combing the information from input images. According to the application or need, image fusion technique can be used. Number of techniques with varieties of solutions is available for image fusion process. And thus it becomes difficult task to find an optimal solution for image fusion. Genetic algorithm is an optimization technique used for searching solution for large number of complex problems [15]. This paper gives the quality index of image fusion obtained using the combinations of different selection methods and crossover techniques in genetic algorithm. These techniques have been compared using root mean square error to obtain information about relative performance. The experimental result on some standard test images shows that performance parameters i.e. root mean square error (RMSE) and peak signal to noise ratio (PSNR) are good for multifocus and multisensor image fusion.
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Optimization of Graph Coloring to Determine Culinary Tourism in Samarinda
Статья научная
A problem that often arises is that many places to eat are available, making everyone confused to choose a place to eat and takes a long time to decide on where to eat. Because it requires a system and methods that can be applied to recommend places to eat. Application recommendations for places to eat in this final assignment were made to help everyone in finding a place to eat with the same menu choices. The method used is the Graph Tinting Method, with the application development method used is Waterfall consisting of data analysis, technology analysis, system analysis, information analysis, and user analysis. The results of this study are the making of a restaurant determination application that can recommend places to eat with the same menu. Users can enter menus according to their wishes, then the application will recommend places to eat using a simple line coloring algorithm at the point. After processing, the application will be able to display the results of recommendations for restaurants with the same menu.
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Optimization of MUSIC and Improved MUSIC Algorithm to Estimate Direction of Arrival
Статья научная
The signal processing applications are limited with high-resolution signal parameter estimation. Therefore the Direction of Arrival estimation algorithm needs to be effective and efficient in order to improve the performance of smart antennas. This paper presents the simulation for a subspace based DOA estimation algorithm with high resolution. MUSIC (Multiple signal classification) and the IMUSIC (Improved MUSIC) are presented and optimized by varying various parameters. The basic MUSIC algorithm is ineffective in estimating the incoming coherent signals. The new improved MUSIC algorithm overcomes this ineffectiveness and correctly estimates the related signals with improved accuracy. The improved version of MUSIC algorithm is brought about by taking into account the conjugate of the data matrix for MUSIC algorithm and then reconstructing it. The various factors like the number of array elements, number of snapshots, varying the distance between array elements, varying SNR and the difference in arrival angles can bring about better resolutions. The comparisons for MUSIC and Improved MUSIC algorithm are widely discussed.
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Optimization of Matched and Mismatched Filters in Short Range Pulse Radars using Genetic Algorithm
Статья научная
Matched and mismatched filters are considered important parts of a radar signal processing unit. In this paper, we present an approach to optimize the matched filters and mismatched filters in short range pulse radars. For radar, the matched filter coefficients are the complex conjugates of transmitted code. We used binary phase codes as transmitted pulse. The disadvantage of binary phase codes is having high sidelobe levels in the output of correlation function. Thus, we decided to use optimization algorithms for finding binary phase codes with minimum peak sidelobe levels (MPS). After that, we succeeded in producing mismatched filter coefficients (Mis-co) for each code using floating point genetic algorithm (FGA) and we could generate and test the filter coefficients with maximum peak to sidelobe level ratio (PSR). For testing the filter, we plotted ambiguity function for each set of coefficients and tested the filter with Doppler shift.
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Статья научная
Optimization is one of the techniques used in the estimation of projects to obtain the optimal parameter sequence at different levels for the best project conditions, such as size, duration and function points. In this paper, to select the significant process parameter sequence at different levels, a combination of Grey Relational Analysis (GRA) and Taguchi method applied during the estimation. This parameter sequence is essential for the industries in producing quality product at a lower cost. Taguchi method is used to improve the product quality and reduce the cost. Among the various methods of Taguchi as a standard Orthogonal Array (OA) produces better parameters to be considered at different levels. This paper uses L16 Orthogonal Array (OA) whose efficiency is proven in the experimental results. Here, a variant of GRA, GRG has been used to assign grades for projects in the dataset. Finally, the optimized process parameter sequence at different levels is obtained through the application of GRG over L16 Orthogonal Array (OA). In this paper, Grey-Taguchi method is implemented to find out the levels of software process parameters such as Duration, KSLOC, Adjustment Function Points and Raw Function Points necessary for minimizing software effort. Experimental results show that parameter levels suggested by Grey-Taguchi method result in improved GRG, which results in better software effort estimation.
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Optimized Low Power Dual Edge Triggered Flip-flop with Speed Enhancement
Статья научная
This paper gives a novel low-power approach with pulse generating circuits using dual edge triggered flip-flops. By doing so, flip-flop might operate at 1.2Volts, with the novel quick latch and conditional precharging. This paper aims at a new proposed low power dual edge triggered flip-flop with speed enhancement to achieve low power consumption with a shorter delay in power usage, hence, it is well suited for low-power digital system applications. The new proposed low power dual edge triggered flip-flop also aims at comparison with the three DETFF, Static Output Controlled Discharge Flip-Flop (SCDFF), Dual Edge Triggered Static Pulsed Flip-flop (DETSPFF), and Pervious work on Dual Edge Triggered flip-flop, proves to achieves with reduction in numbers of transistors in the stack and increases the number of charge-paths results in a faster operational speed. According to simulation on Spectre simulator, it has been observed that total power consumption of proposed flip flop at 0.67 switching activity is 30.16 % and 27.36 % less than that of previous arts DSPFF and SCDFF respectively. Clock-gated sense-amplifier is incorporated to reduce power consumption at low switching activity. The simulation is done using Cadence tool with 45nm standard CMOS technology.
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Статья научная
This paper investigates the application of adaptive Bacteria Forging Algorithm (BFA) to design optimal controllers for voltage stability of off-grid hybrid power system (OGHPS).Voltage fluctuations will have great impact on the quality of power supply. Voltage rise/drop depends on the surplus / shortage of reactive power in the system, hence it has become extremely important to manage the reactive power balance for voltage control in the off-grid hybrid power system. The off -grid hybrid power system considered in this work as a test system, consist of an Induction generator (IG) for wind power systems, Photo-Voltaic (PV) system with inverter, Synchronous generator (SG) for diesel power generation and composite load. The Over-rated PV inverter has ample amount of reactive power capacity while sourcing PV real power. Two control structures are incorporated, to regulate system voltage. The first control structure is for the reactive power compensation of the system by inverter, by controlling the magnitude of inverter output voltage and the second control structure is for controlling the SG excitation by an automatic voltage regulator (AVR) and hence the load voltage. Both control structures have proportional-integral (PI) controller. Both control loops are coordinated by tuning their parameters optimally and simultaneously using an adaptive Bacterial forging optimization algorithm. Small signal model of all components of OGHPS is simulated in SIMULINK, tested for reactive load disturbance and /or wind power input disturbance of different magnitudes to investigate voltage stability.
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Optimum Features selection by fusion using Genetic Algorithm in CBIR
Статья научная
The evaluation of the performance of the Content Based Image Retrieval is undertaken for the consideration in this paper. Here the point of the discussion is the performance of the CBIR system using object oriented image segmentation and the evolutionary computational technique. The visual characteristics of the objects such as color, intensity and texture are extracted by the conventional methods. Object oriented image segmentation along with the evolutionary computational technique is proposed here for Image Retrieval Algorithm. Unsupervised Curve evolution method is used for object oriented segmentation of the Image and genetic Algorithm is used for the Optimum Classification and reduction in the Feature dimensionality. The Algorithm is tested on the images which are characterized by the low depth. The Berkeley database is found to be suitable for this purpose. The experimental result shows that the Genetic Algorithm enhances the performance of this Content Based Image Retrieval and found to be suitable for optimization of features selection and compression technique for Feature space.
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Optimum Fuzzy based Image Edge Detection Algorithm
Статья научная
Edge detection is important in image processing to aid operations such as object classification and identification amongst others. This is soley to improve interpretability of the image. Common edge detection techniques such as Sobel, Prewittt, Canny, Laplacian of Gaussian (LOG), Robertss and Zero-Crossing has attracted the attention of researchers to perform a comparative analysis on these techniques excepts fuzzy, using different type of images. Fuzzy logic based edge detection algorithms development and comparison with existing algorithm became important due to the fact that the pixels’ boundaries identifying image degs are crystal clear as expected, hence other edge detection algorithms using crisp values will be omitting some vital information pixels, this impairs the quality of the image edge detected and further application through proper interpretation. This research further extends the investigation of edge detection techniques optimality, through comparing Sobel, Prewittt, Canny, Laplacian of Gaussian (LOG), and Robertss edge detection algorithms with our proposed fuzzy based edge detection algorithm designed using MATLAB. The result indicated that the novel fuzzy based edge detection algorithm developed in this research outperforms the Canny, Sobel, Prewittt, Robertss and LOG edge detection algorithms in three different experiments with different images
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Palatal Patterns Based RGB Technique for Personal Identification
Статья научная
Biometric system is an alternative way to the traditional identity verification methods. This research article provides an overview of recently / currently used single and multiple biometrics based personal identification systems which are based on human physiological (such as fingerprint, hand geometry, head recognition, iris, retina, face recognition, DNA recognition, palm prints, heartbeat, finger veins, footprints and palates) and behavioral (such as body language, facial expression, signature verification and speech recognition) characteristics. This paper focuses on RGB based palatal pattern analysis of persons and the proposed technique uses RGB values with silhouette computes of palatal patterns for identifying a person. We have tested our proposed technique for palatal patterns of 50 persons including males & females and it is observed that RGB values based silhouette technique are accurately identifying the persons on the basis of their palatal patterns. For each person seven palatal images were taken. Out of these seven palatal images, four images were used for training dataset and last three palatal patterns were used for identifying the persons. The proposed technique is reliable & secure and it is a foolproof method which is clearly differentiating the persons on the basis of their palatal patterns.
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Parallel Implementation of Texture Based Image Retrieval on The GPU
Статья научная
Most image processing algorithms are inherently parallel, so multithreading processors are suitable in such applications. In huge image databases, image processing takes very long time for run on a single core processor because of single thread execution of algorithms. Graphical Processors Units (GPU) is more common in most image processing applications due to multithread execution of algorithms, programmability and low cost. In this paper we implement texture based image retrieval system in parallel using Compute Unified Device Architecture (CUDA) programming model to run on GPU. The main goal of this research work is to parallelize the process of texture based image retrieval through entropy, standard deviation, and local range, also whole process is much faster than normal. Our work uses extensive usage of highly multithreaded architecture of multi-cored GPU. We evaluated the retrieval of the proposed technique using Recall, Precision, and Average Precision measures. Experimental results showed that parallel implementation led to an average speed up of 140.046×over the serial implementation. The average Precision and the average Recall of presented method are 39.67% and 55.00% respectively.
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