Статьи журнала - International Journal of Image, Graphics and Signal Processing
Все статьи: 1056
The Research of the Measures Algorithm of the Parameter of the Cutter
Статья научная
Edge detection is the most basic problem in the process of image processing. The precision of traditional edge detection algorithm is not very high, it unable to meet the high precision need of modern industrial test technology. In order to overcome the deficiency, this text proposed subpixel edge detection algorithm based on the function curve fitting-Gauss fitting of gradient direction sub-pixel edge detection algorithm. According to the gradient distribution of the image, this text use gauss curve fitting the edge in order to realize the sub-pixel location. This text compared this algorithm with sub-pixel edge detection based on the LOG operator and sub-pixel edge detection based on the quadratic, and draw that this algorithm not only have the short running time and high efficiency, but also has proved that the algorithm has rotation invariant through the experiment. It is that pattern recognition and picture measure the important pretreatment means in the course to follow the method at the border, contradiction at accuracy and speed that but follow the method and exist at the traditional border. To above-mentioned problems, this text proposes following algorithms at the border based on model, and then try to get the diameter of the cutter. The experiment shows this algorithm at the realization border that can be very good and follows, measure the comparison of the algorithm through two kinds of diameters, drawing the running time of least square method shorter, efficiency is relatively high.
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The Unwanted Emission Signals in the Context of the Reconstruct Possibility of Data Graphics
Статья научная
In its operation, every electrical device generates electromagnetic disturbance signals. They can be due to the operation of components of the device (step motors, heaters, control circuits, or electronic circuits). Quite often such signals have the characteristics of the data processed on such devices. They can have the form of a text. In each case, such signals are undesirable. However, they can be used to reproduce such data or, in other word, to conduct the process of electromagnetic infiltration. In the case of video signals (graphic mode of a computer, a laser printer), then the reproduced data can be presented in the form of graphic images that can be easily assimilated by people. Such images are transformed in order to find the data that is of interest. Reproduction of such data may lead to a disclosure of classified information. There are many solutions that should counter the process of reproduction of such data. Such solutions are implemented in the design of equipment and influence, to a lesser or greater extent, the appearance of the equipment, as well as the related organizational methods. A new method that can be used in electromagnetic protection of process data is a software solution. It involves the use of appropriate computer fonts. The article presents the possibilities related to shaping the form of video signals. For this purpose, appropriate shapes of the letter characters of computer fonts were recommended. Unlike characters in standard fonts (Arial and Times New Roman), they do not have the unique decorative elements (serif), such as hooks, connectors, heels, arches, and ribbons, and consist of only vertical and horizontal lines [5]. There are no slanted and crooked lines. Due to this, the characters are often very similar. This greatly contributes to the impossibility to differentiate between the letter characters in the reproduced image that is filled with noise and numerous disturbances. The graphic elements being searched, having the form of strings of letters, cannot be read. The digital image processing methods intended to improve the quality of the image are quite ineffective. In search for graphic characters, such as computer font letter and digit characters, one can use methods based on the similarity of the standard with a portion of the analyzed image. However, when special fonts are used, the correlation method generates many false decisions, which also prevents reading text data.
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Статья научная
To obtain solar energy from solar photo-voltaic panels is not a new task now a days. Solar panels are designed to give their maximum possible output when exposed to the solar radiations. The operating conditions of solar panels affected by the atmospheric conditions like dust, dirt, solar INSOLATION, temperature etc. Here the effect of cement and bird deposits on the surface of solar panels is considered. Temperature rise due to cement and bird deposits develop hot-spots and affects the electrical power output of the solar panel. The cement and bird deposits can be seen by visually on solar panel surface but their effect can not be visualized by naked eye. The infrared THERMOGRAPHY helps to analyze these effects by using thermal imaging camera. This paper focus to study the temperature effects of cement and bird deposition on solar panel surface by capturing thermal images along with analyzing the thermal images using MATLAB digital image processing for better understanding. Image segmentation for cement and bird deposits is performed using watershed transform to achieve the desired region of interest from thermal images.
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Статья научная
Solar batteries are the essential component in an off-grid solar photovoltaic generation system and used for the purpose of storage. Normally lead acid batteries are used for solar applications and are placed in a battery room where the temperature must be maintained with in safe working limits. The temperature of battery depends on several factors like ambient temperature, load current drawn by the battery, sulphur deposition terminals, charging and discharging cycles. When temperature of a battery increases beyond safe limit problems of heating arises. Heating reduces the battery life and may be one of the reasons of explosion in batteries. The ambient temperature measuring device used in battery room is not sufficient to measure the heat generated by batteries. Installation of a normal camera in battery room is capable to monitor the smoke or spark in battery components but not the amount of temperature so it is also not fulfilling the need. Thermal imaging camera captures heat coming out from a battery and produces a thermal image with temperatures associated with it. This thermal image is used for representing high and low temperatures with a range of maximum and minimum values of temperature. In this paper a heated battery is identified in a battery room for solar photovoltaic generation system and thermal image analysis is performed to determine the regions of high temperature with the help of image segmentation and 3D temperature plot. The image segmentation is done using marker based watershed transform technique to achieve the heated region of interest from thermal image and 3D temperature plot shows the area of maximum temperature with location in thermal image of heated solar battery.
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Three dimensional modeling and animation of a new maglev ship and its study with computer vision
Статья научная
This In the present study, a new type of ship is designed based on the theory of magnetic levitation (Maglev). The structural layout of the proposed ship is modified to adopt the maglev technology. The objective of designing this ship is to assist merchandise and travelers over a long distance in a short period of time. The design and size of this ship is made in such a manner that it has got airplanes landing and take-off facility. According to the theory of magnetic levitation, it travels with negligible friction (ideally frictionless) on a magnetic guideway with high speed and expected safety. An electro-dynamic suspension (EDS) system for magnetic levitation has been used and it would reduce friction on a large scale and generate strong force for both lifting and propulsion purposes and it would also allow the very high speed of travel. High-temperature superconductor (HTS) wires with cryogenic structure are utilized as a part of the configuration of a couple of segments of the maglev ship. The attraction and repulsion force between superconductor magnets and permanent electromagnets are the key factors behind such operation. Computer vision study helps to track the moving object to find whether the object is moving or not. The proposed method has been found to give the acceptable result to identify the moving object.
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Three phase induction motor drive using hybrid fuzzy pi controller based on field oriented control
Статья научная
The objective of this paper is to present the three phase induction motor drive using the cooperation of fuzzy logic controller and proportional plus integral (PI) controller as a hybrid run on field oriented control (FOC) for improving the performance of rotor speed. The system is fed to a three phase induction motor by voltage source inverter that is used space vector modulation (SVM) technique. This system is implemented with the control system on dSPACE programming which is supported by MATLAB/Simulink through a dSPACE -ds1140 interfacing module. In the implementation, the conventional PI controllers are replaced by hybrid fuzzy PI controllers of both an outer speed control loop and two inner currents control loops that are controlled stator flux and rotor torque of the induction motor. The experimental results are compared with conventional PI controllers. As a result, the performance of design model by hybrid fuzzy PI controller is better than the conventional PI controllers.
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Three-dimensional Morphological Analysis for Geological Bodies and Application
Статья научная
To address the spatial Morphological analysis of complex geological bodies in stereoscopic quantitative prediction of concealed ore bodies, a three-dimensional morphological analysis method for geological bodies based on 3-dimensional raster model under visualization environment was put forward by combining mathematical morphology with Euclidean distance transform theory. Firstly, the 3-dimensional visualization models for geological bodies were constructed on the basis of the 3-dimensional geological modeling (3DGM) technology; Secondly, the algorithm for extracting the surface shape trend of geological body with the 3-dimensional raster model was proposed by using mathematical morphology filtering. By the combination of morphological filtering, global set operation and three-dimensional Euclidean distance transform, the models for the quantitative analysis and hierarchical extraction of the shape undulance were established. Lastly, as a case study, the three-dimensional morphological analysis method was applied in analyzing quantitatively the Xinwuli magmatic body in Fenghuangshan ore field in Tongling, Anhui Province. By means of the calculation model of Euclidean distance field, the quantitative extraction of the shape trend and shape undulance as well as the angle between geological interface and trend surface, as the quantitative indexes of geological ore-controlling factors, were achieved after building the 3D raster models of the magmatic body. The results show that the morphological analysis method is feasible to calculate various morphological parameters of complex geological bodies and extract quantitative indexes of geological ore-controlling factors successfully for stereoscopic quantitative predication of concealed ore bodies.
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Three-dimensional Region Forgery Detection and Localization in Videos
Статья научная
Nowadays, with the extensive use of cameras in many areas of life, every day millions of videos are uploaded on the internet. In addition, with rapidly developing video editing software applications, it has become easier to forge any video. These software applications have made it challenging to detect forged videos, especially with forged videos have duplication of three-dimensional (3-D) regions. Recently, there has been increased interest in detecting forged videos, but there are very limited studies to detect forged videos which were duplicated 3-D regions. So, our research focused on this weakness and proposed a new method, which can be used for detecting and locating 3-D duplicated regions in videos based on the phase-correlation of 3-D regions residual more efficiently. To evaluate the efficiency of the proposed method, we experimented with two realistic datasets VFDD-3D and REWIND-3D. The results of the experiments proved that the proposed method is efficient and robust for detecting small 3-D regions duplication and frame sequences duplication, especially localization of duplication forgery in videos has shown impressive results.
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Threshold based Image Fusion in Dual Tree Complex Wavelet Domain
Статья научная
Image fusion is a popular application of image processing which performs merging of two or more images into one. The merged image is of improved visual quality and carries more information content. The present work introduces a new image fusion method in complex wavelet domain. The proposed fusion rule is based on a level dependent threshold, where absolute difference of a wavelet coefficient from the threshold value is taken as fusion criteria. This absolute difference represents variation in the image intensity that resembles the salient features of image. Hence, for fusion, the coefficients that are far from threshold value are being selected. The motivation behind using dual tree complex wavelet transform is due to failure of real valued wavelet transform in many aspects. Good directional selectivity, availability of phase information and approximate shift invariant nature of dual tree complex wavelet transform make it suitable for image fusion and help to produce a high quality fused image. To prove the strength of the proposed method, it has been compared with several spatial, pyramidal, wavelet and new generation wavelet based fusion methods. The experimental results show that the proposed method outperforms all the other state-of-the-art methods visually as well as in terms of standard deviation, mutual information, edge strength, fusion factor, sharpness and average gradient.
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Статья научная
In synthetic aperture radar (SAR) imaging system speckle is modeled as a multiplicative noise which limits the performance of SAR image processing systems. In the literature, several SAR image despeckling algorithms have been presented, among them two simple, yet effective, approaches are using thresholding and Bayesian estimation in transform domains. In this article, we try to provide proper answer to this question: which one of these two despeckling methods works better? To this aim, we first introduce a new thresholding function with two thresholds, and show that when thresholds are determined through optimization procedures, an improved denoising performance in terms of joint speckle removal and edge saving efficiencies can be achieved. However, still a Bayesian LMMSE/MAP estimator can provide greater speckle removal efficiency in test images with high speckle power, and some thresholding methods produce better edge saving efficiency. Hence, aiming at joint exploitation of the superior edge saving ability of thresholding estimator and greater speckle removal efficiency of Bayesian estimator, we next propose the idea of using a combined despecking algorithm. The new denoising methods are applied for despeckling of true SAR images in the nonsubsampled contourlet transform domain and the situations they achieve superior performance have been highlighted.
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Tomographic Convex Time-Frequency Analysis
Статья научная
In this paper we aim to solve a problem of image reconstruction in tomography. In medical imaging, patients suffer from taking high dose of radioactive drug in order to get a well-qualified image. Our goal is to reduce this dose of radioactive drug given to the patients in PET scan and to get a well-qualified image. We use to modeling this problem using a convex function to minimize. In tomography, real problem requires a positive constraint and may get a blurred image due to poisson noise. Then, in order to get back a non blurred image of human body, we add to this function a wavelet regularization which is a non differentiable function. We introduce specific algorithms to get the minimum of the global function obtained. After presenting the classic algorithms with their conditions to solve the problem we find that Chambolle Pock's algorithm requires less properties than these algorithms and gives good results. Then, we propose its computation method with the proof.
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Towards Query Efficient and Derivative Free Black Box Adversarial Machine Learning Attack
Статья научная
While deep learning has shown phenomenal success in many critical applications such as in autonomous driving and medical diagnosis, it is vulnerable to black box adversarial machine learning attacks. Objective of these attacks is to mislead a classifier in making mistakes. Hard Label attacks are those in which an adversary has access only to the top-1 prediction label and has no knowledge about model parameters or gradient loss. Secondly, for security concerns, the number of model queries that an attacker can perform for evaluation are restricted. In this paper, we propose a novel nature-inspired optimization algorithm for generating adversarial examples. Proposed algorithm is derivative-free, meta-heuristic algorithm. It searches for optimum adversarial examples in high-dimensional image space using simple arithmetic operations inspired by Brownian motion of molecules in fluids and gases. Experiments with CIFAR-10 image dataset yielded encouraging results with a query budget of less than 1000 and with a minimal distortion to original image. Its performance was determined to be comparable and exceeded in some cases compared to previous state of the art attacks.
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Статья научная
An electrocardiogram (ECG) machine is a device that checks the patient’s heart rhythm and electrical activity. This is done by attaching sensors on the skin of the patients. But the problem with these machines is that, these are expensive and not portable. Thus it is difficult to use these machines in the rural or remote areas of developing countries like Bangladesh where the issue of portability and cost arises. In this paper, the problem of cost and portability is addressed. We propose a complete solution for a low-cost portable ECG monitoring from recording to report generation for patients including real-time ECG traces on screen with storage options and calculation of all necessary diagnostics parameters for helping the doctors to make decision. This type of ECG machines could be used in hospitals, homes, villages or even in a disaster area. The system designed in this paper includes a PC/Laptop, as these devices are now widely available, at least available at hospitals and health care centers, even in rural/remote areas of Bangladesh. With this, a significant difference can be made against heart diseases.
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Tracking of Moving Object Using Centroid based Prediction and Boundary Tracing Scheme
Статья научная
Object tracking has always been a hotspot in the field of computer vision and has myriad applications in the real world. A major problem in this field is that of the successful tracking of a moving object undergoing occlusion in its path. This paper presents centroid based tracking scheme of a moving object without any apriori information of its shape or motion. Once the boundary of the object of interest is obtained, the centroid is calculated from its first order moments. This centroid is further utilized to detect the partial occlusion of test object by some other still or moving object in image frame. In case occlusion is detected, the new centroid location of moving object is predicted for subsequent video frames. The proposed algorithm is able to successfully detect moving object undergoing partial or total occlusion. Experimental results of our algorithm are compared with a popular tracking technique based on Mean Shift tracking algorithm.
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Traffic video enhancement based vehicle correct tracked methodology
Статья научная
In this paper, an enhancement based traffic video has been proposed in the state of the art of computer vision. The main target is to develop a decision making criteria for removing the most probable video degradations. Such traffic video degradations would have an adverse impact on the transportation system. In order to establish the appropriate analysis, three types of video degradations have been added to the test video; salt and pepper noise, Gaussian noise, and speckle noise, we have simulated rainy, fog, and darkness conditions for the traffic video. First of all, back ground subtraction and Kalman filter techniques have been used for detecting and tracking vehicles respectively. By using such algorithms, it would be easily to estimate average number of assigned tracks which express the efficacy of correct detection and prediction of vehicles in each frame. Furthermore, video degradations would be applied in order to studying its effect on the average number of assigned tracks which would be deviated than noiseless video. Spatial filtering system has been applied to state the most suitable filter mask which satisfy the least deviation in the average number of assigned tracks. Experimental results show that median filter satisfies the least deviation in all cases of video degradations.
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Transfer Subspace Learning Model for Face Recognition at a Distance
Статья научная
Many machine learning algorithms work under the assumption that the training and testing data are drawn from the same distribution. However, in practice the assumption might not hold. Transfer subspace learning algorithms aims at utilizing knowledge gained in source domain to learn a task in target domain. The main objective of this work is to apply transfer subspace learning framework on face recognition task at a distance. In this paper we identify face recognition at distance as a transfer learning problem. We show that if the face recognition task is modeled as transfer learning problem, the overall classification rate is increased significantly compared to traditional brute force approach. We also discuss a data set which is unique and meant to advance this research. The novelty of this work lies in modeling face recognition task at distance as a transfer subspace learning problem.
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Transformation of Classical to Quantum Image, Representation, Processing and Noise Mitigation
Статья научная
Quantum and classical computers have drastically different image representations. In a classical computer, bits are used. However, in a quantum computer, qubits are used. In this paper, the quantum image representation is the similar as the classical image representation. To represent quantum images, qubits and their associated properties have been used. Quantum imaging has previously been done via superposition. As a result, quantum imaging implemented using the superposition feature. Unitary matrices are then used to represent quantum circuits. For the quantum representation, we've gone with a modest image. To create quantum circuits, IBM's Qiskit software and Anaconda Python was used. On an IBM real time computer and an Aer simulator, a quantum circuit with 10,000 shots runs. Noise has been reduced more in the IBM real time computer than in the IBM Aer simulator. As a result, the Aer simulator's noise and qubit errors are higher than the IBM real time computer's. Quantum circuit design and image processing are both done with Qiskit programming, which is an appendix at the end of the paper. As the number of shots raise, the noise level decreases even further. Noise and qubit errors increase when the image operates at a low number of shots. Quantum image processing, noise reduction, and error correction done by circuit computation shots increase. Quantum image processing, representation, noise reduction, and error correction all make use of the quantum superposition concept.
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Статья научная
Realistic knowledge of rainfall characteristics and modeling parameters such as size, shape, and drop size distribution is essential in numerous areas of scientific, engineering, industrial and technological applications. Some key application areas include, but not limited to microphysics analysis of precipitation composition phenomenon, weather prediction, signal attenuations forecasting, signal processing, remote sensing, radar meteorology, stormwater management and cloud photo detection. In this contribution, the influence of rain intensity on raindrop diameter and specific attenuation in Lokoja, a typical climate region of Nigeria is investigated and reported. Three different rain rates classes obtained due to heavy rainfall depth, heavy rainfall depth, and heavy rainfall depth have been explored for the raindrop size distribution analysis. The three-parameter lognormal and Weibull models were utilised to estimate the influence of rain rates on the drop sizes and specific rainfall attenuation in the study location. For Lognormal model, the maximum raindrop concentration occurred approximately at diameter of 1 mm before showing downfall performance trends as the drop diameter increases. In the case of Weilbull model, the maximum raindrop concentration occurred at different drop diameter with the three rain rate classes, before showing downfall concentration trends with increasing rain drop diameter values. By means of the two models, the highest raindrops concentration values attained in correspondence with the specific rain attenuation were made by drop diameters not more than 2.5 mm. In terms of rain rate, specific attenuation and frequency connection, the results disclose that attenuation of propagated electromagnetic waves increases at increasing rainfall depth and increasing operating frequency bands. The results also disclose that the specific attenuation is directly proportional to the increase in rain intensity levels in correspondent with the operational frequency. As a case in point, at 4GHz frequency, the attenuation level of about 20 dB/km level is attained for mean, minimum and maximum rain rates of 29.12, 12.23 and 50.22 mm/hr, respectively. But as the frequency increased from 4GHz to 20GHz, the attenuation level almost doubles from 20 to 45dB/km at still same rain rates. The above performance is so, because at higher radio-microwave frequencies, the wavelength of the propagated electromagnetic waves approaches the mean diameter of the raindrop. The results display gradual increase in attenuation levels as the diameter rain drop sizes and intensity increases or become broader. The attenuation grows because the raindrops interfere, distort, absorb and scatter major portion of the microwave energy. However, the gradual trend in the attenuation level increase becomes slower and tending to logarithm stability at larger rain drop values. This may suggest that the attenuation level may come to equilibrium state at higher rain drop diameters. The resultant outcome of this work can assist microwaves communication engineers and relevant stakeholders in the telecommunication sector with expedient information needed to manage specific attenuation problems over Earth–space links communication channels, particualry during rainy seasons.
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Статья научная
Breast cancer is most common and leading cause of death among women. With improvement in the imaging modalities it is possible to diagnose the cancer at an early stage moreover treatment at an early stage reduces the mortality rate. B-mode ultrasound (US) imaging is very illustrious and reliable technique in early detection of masses in the breast. Though it is complimentary to the mammography, dense breast tissues can be examined more efficiently and detects the small nodules that are usually not observed in mammography. Segmentation of US images gives the clear understanding of nature and growth of the tumor. But some inherent artifact of US images makes this process difficult and computationally inefficient. Many methods are discussed in the literature for US image segmentation, each method has its pros and cons. In this paper, initially region merging based watershed and marker-controlled watershed transforms are discussed and implemented. In the subsequent sections we proposed a method for segmentation, based on clustering. Proposed method consists of three stages, in first stage probability images and its equalized histogram images are obtained from the original US images without any preprocessing. In the next stage, we used VQ based clustering technique with LBG, KPE and KEVR codebook generation algorithm followed by sequential cluster merging. Last stage is the post processing, where we removed unwanted regions from the selected cluster image by labeling the connected components and moreover used morphological operation for closing the holes in the final segmented image. Finally, results by our method are compared with initially discussed methods.
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Two-Dimensional Parameters Estimation
Статья научная
A parametric approach algorithm based on maximum likelihood estimation (MLE) method is proposed which can be exploited for high-resolution parameter estimation in the domain of signal processing applications. The array signal model turns out to be a superposition of two-dimensional sinusoids with the first component of each frequency doublet corresponding to the direction of the target and second component to the velocity. Numerical simulations are presented to illustrate the validity of the proposed algorithm and its various aspects. Also, the presented algorithm is compared with a subspace based technique, multiple signal classification (MUSIC) to highlight the key differences in performance under different circumstances. It is observed that the developed algorithm has satisfactory performance and is able to determine the direction of arrival (DOA) as well as the velocity of multiple moving targets and at the same time it performs better than MUSIC under correlated noise.
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