Статьи журнала - Компьютерная оптика
Все статьи: 2346
Robust hybrid technique for moving object detection and tracking using cartoon features and fast PCP
Статья научная
In various computer vision applications, the moving object detection is an essential step. Principal Component Analysis (PCA) techniques are often used for this purpose. However, the performance of this method is degraded by camera shake, hidden moving objects, dynamic background scenes, and / or fluctuating exposure. Robust Principal Component Analysis (RPCA) is a useful approach for reducing stationary background noise as it can recover low rank matrices. That is, moving object is formed by the low power models and the static background of RPCA. This paper proposes a simple alternative minimization algorithm to fix minor discrepancies in the original Principal Component Pursuit (PCP) or RPCA function. A novel hybrid method of cartoon texture features used as a data matrix for RPCA taking into account low-ranking and rare matrix is presented. A new non-convex function is proposed to better control the low-range properties of the video background. Simulation results demonstrate that the proposed algorithm is capable of giving consistent random estimates and can indeed improve the accuracy of object recognition in comparison with existing methods.
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Статья научная
Scattering potentials of hollow particles with ellipsoid-, cylinder- and parallelepiped-like shapes and adjustable edge sharpness are introduced as a difference of two 3D multi-Gaussian functions with suitable parameters. The far-zone intensity distributions generated on weak scattering from such potentials are shown to depend on the scatterer’s boundary thickness, edge softness as well as on its size relative to the wavelength. Possible extension to potentials formed by nested shells of the same or different types and potentials with semi-hollow center is outlined.
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Screen recapture detection based on color-texture analysis of document boundary regions
Статья научная
This paper examines a presentation attack detection when a document recaptured from a screen is presented instead of the original document. We propose an algorithm based on analyzing a moiré pattern within document boundary regions as a distinctive feature of the recaptured image. It is assumed that the pattern overlapping the document boundaries is a recapture artifact, not a match between document and background textures. To detect such a pattern, we propose an algorithm that employs the result of the fast Hough transform of the document boundary regions with enhanced pattern contrast. The algorithm performance was measured for the open dataset DLC-2021, which contains images of mock documents as originals and their screen recaptures. The precision of the proposed solution was evaluated as 95.4 %, and the recall as 90.5 %.
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Security detection of network intrusion: application of cluster analysis method
Статья научная
In order to resist network malicious attacks, this paper briefly introduced the network intrusion detection model and K-means clustering analysis algorithm, improved them, and made a simulation analysis on two clustering analysis algorithms on MATLAB software. The results showed that the improved K-means algorithm could achieve central convergence faster in training, and the mean square deviation of clustering center was smaller than the traditional one in convergence. In the detection of normal and abnormal data, the improved K-means algorithm had higher accuracy and lower false alarm rate and missing report rate. In summary, the improved K-means algorithm can be applied to network intrusion detection.
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Статья научная
3D mesh segmentation has become an essential step in many applications in 3D shape analysis. In this paper, a new segmentation method is proposed based on a learning approach using the artificial neural networks classifier and the spectral clustering for segmentation. Firstly, a training step is done using the artificial neural network trained on existing segmentation, taken from the ground truth segmentation (done by humane operators) available in the benchmark proposed by Chen et al. to extract the candidate boundaries of a given 3D-model based on a set of geometric criteria. Then, we use this resulted knowledge to construct a new connectivity of the mesh and use the spectral clustering method to segment the 3D mesh into significant parts. Our approach was evaluated using different evaluation metrics. The experiments confirm that the proposed method yields significantly good results and outperforms some of the competitive segmentation methods in the literature.
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Sensor with enhanced performance based on photonic crystal with a defect layer
Статья научная
We propose an improved structure of an optical biosensor based on a photonic crystal with a defect layer, which can detect the concentration of organic contaminants in water by defect mode shift. We investigated 4 types of defective photonic crystals with different arrangements of layers inside the perfect photonic crystals and their impact on the performance of the sensor. The sensitivity and amplitude of defect mode were examined as a function of defect layer thickness. Also, the peculiarities of edge modes in the presence of defect layer were investigated. Finally, we obtained a characteristic equation to determine the wavelengths of defect modes for an arbitrary 1D photonic crystal with an isotropic defect inside.
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Simulation of a long-haul fiber optic link with a two-mode optical fiber
Статья научная
Modern telecommunication networks approach the capacity crunch, which is associated with the so-called nonlinear Shannon limit. So, the passage to fiber optic links with few-mode optical fibers is considered as an alternative solution of the described problem concerned with high nonlinearity of conventional commercial single-mode optical fibers. Presently, various designs of few-mode optical fibers have been known, with the recently published works presenting experimental results demonstrating their potentialities for long-haul fiber optic links. A lot of models of long-haul fiber optic links with few-mode optical fibers have been developed based on which features of a few-mode optical fiber transport network were numerically simulated. This work presents the results of simulation of a 6000-km long-haul fiber optic link with a two-mode optical fiber and 100-km-per-span Erbium doped fiber optic amplifiers system under 100 Gbps DP-DQPSK data transmission. We studied the use of particular linearly polarized modes and optical vortices for signal transmission. The computation results were compared with the simulation of the same fiber optic link with a single-mode optical fiber under the identical conditions.
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Статья научная
Features of laser-assisted warm forming of dual phase steel DP1000 are determined. Simulation of forming processes with local heating is performed. In the simulation procedure, the forming parameters of three dimensional forming were adapted to keep them within tolerable limits even in critical areas as well as identifying the localization and type of critical stresses. The capabilities of Abaqus were extended by use of the Python language to independently evaluate selected element strains, the position of deformed elements within the forming limit diagram and user-defined failure criteria. The simulation led to an adapted forming process permitting a significantly increased bulge forming depth by local laser heating of the forming zones. The developed simulation model shows a satisfactory conformity with experiments, performed using a fibre-coupled laser with a wavelength of 1070 nm and a maximum output power of 1500 W, and a servo bending press TRUMPF TruBend 7018. The required distribution of the laser beam energy can be obtained by using diffractive optical elements. The use of the model for technological operations opens up possibilities not only for the solution of the presented specific objective of laser assisted warm forming, but also for others applications.
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Статья научная
One of important tasks of the day is increasing the efficiency and decreasing the cost of the silicon solar cells. There is method of introducing of metal nanoparticles into solar cells to improve its absorption and reduce transmission as well as reflection coefficients. When metal nanoparticles are introduced into silicon solar cell, nanoplasmonic effect will occur. Nanoplasmonic effect lead to modification of light spectrum and generation of extra hot electrons. Nanoplasmonic effect strongly depends on size of nanoparticles. Therefore, in this paper, effect of gold nanoparticles size on properties of silicon solar cell has been studied by using simulation. Gold nanoparticles with sizes of 4 nm, 6 nm, 9 nm, 11 nm and 21 nm have been input into emitter region of silicon solar cell in order to use both of nanoplasmonic-electric and nanoplasmonic-optic effects for enhancing efficiency of silicon solar cell. Open circuit voltage didn’t change when size of nanoparticles has been changed from 4 nm to 11 nm. It dropped by 0.017 V when size of nanoparticles was 21 nm. Short circuit current has been maximum 6.7 mA/cm2 at nanoparticle size of 11 nm and minimum 3.1 mA/cm2 at nanoparticle size of 21 nm. It has been found from obtained results that gold nanoparticle with size of 11 nm affected significantly on properties of silicon solar cell. Besides, thickness of silicon solar cell can be decreased without dropping of efficiency by introducing gold nanoparticles. Because, main part of photons is absorbed near to metal nanoparticles inputted region.
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Статья
Melanoma skin cancer is one of the most dangerous forms of skin cancer because it grows fast and causes most of the skin cancer deaths. Hence, early detection is a very important task to treat melanoma. In this article, we propose a skin lesion segmentation method for dermoscopic images based on the U-Net architecture with VGG-16 encoder and the semantic segmentation. Base on the segmented skin lesion, diagnostic imaging systems can evaluate skin lesion features to classify them. The proposed method requires fewer resources for training, and it is suitable for computing systems without powerful GPUs, but the training accuracy is still high enough (above 95 %). In the experiments, we train the model on the ISIC dataset – a common dermoscopic image dataset. To assess the performance of the proposed skin lesion segmentation method, we evaluate the Sorensen-Dice and the Jaccard scores and compare to other deep learning-based skin lesion segmentation methods. Experimental results showed that skin lesion segmentation quality of the proposed method are better than ones of the compared methods.
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Статья научная
The SUPPOSe enhanced deconvolution algorithm relies in assuming that the image source can be described by an incoherent superposition of virtual point sources of equal intensity and finding the number and position of such virtual sources. In this work we describe the recent advances in the implementation of the method to gain resolution and remove artifacts due to the presence of fluorescent molecules close enough to the image frame boundary. The method was modified removing the invariant used before given by the product of the flux of the virtual sources times the number of virtual sources, and replacing it by a new invariant given by the total flux within the frame, thus allowing the location of virtual sources outside the frame but contributing to the signal inside the frame.
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Spatiotemporal ecosystem health assessment comparison under the pressure-state-response framework
Статья научная
A spatiotemporal ecosystem health (EH) assessment study is necessary for sustainable development and proper management of natural resources. At present higher rate of human-socio-economic activities, industrialization, and misuse of land are major factors for ecosystem degradation. Therefore this research work used remote sensing (RS) and geographical information system (GIS) technology, under pressure-state-response (PSR) framework with analytic hierarchy process (AHP) weight method based on 29 indicators were analyzed for spatiotemporal EH assessment in Tatarstan and Samara states in Russia from 2010 to 2020. Results indicate continuous degradation of EH in Tatarstan state while in Samara state first decreased and later on an improved ecosystem health condition. This is one of the most innovative analyses work for real-time accurate ecosystem health assessment, mapping, and monitoring as well as protect fragile eco-environment with sustainable development, proper policy-making, and management at any scale and region.
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Study on the Mainardi beam through the fractional Fourier transforms system
Статья научная
In this paper, we introduced the Mainardi beam and indicated its attributes under the Fractional Fourier transform for power variations of Fractional Fourier transform. The results represent that the behavior of the Mainardi beam is similar to that of the Airy beam. The obtained formula is a very powerful tool to describe propagation of a Mainardi beam through the FFT and the FrFT sys-tems. An analytical expression of the Mainardi beam passing through an Fractional Fourier trans-form system presented. The influences of the Fractional Fourier transform, rational order of the Mittag-Leffler function (Fourier transform of the Mainardi function) on the normalized intensity distribution and characteristics of the Mainardi beam in the Fractional Fourier transform system examined. Power of the Fractional Fourier transform (p) and rational order of the Mittag-Leffler function (q) control characteristics of the Mainardi beam such as effective beam size, number, width, height, and orientation of the beam spot.
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Study on the planning of rural land spatial utilization by improved particle swarm optimization
Статья научная
The planning of rural land space utilization is a very important problem. In this paper, the objective function of rural land use planning was analyzed firstly, and then the improved particle swarm optimization (IPSO) algorithm was obtained by improving the inertia weight for solution. The results showed that the land space use in the study area was more reasonable after the planning based on the IPSO algorithm, the forest land and construction land increased, the area of grassland, cultivated land and water area reduced appropriately, the aggregation degree of all types of land improved, and the space distribution was more planned, which was more conducive to production activities. The analysis results verify the effectiveness of the IPSO method in land space use planning, which can improve the efficiency and benefit of land space use, and it can be popularized in practical application.
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Статья научная
In this paper, we continue the study of the quantum cryptographic GG02 protocol, performed using the approach based on the subcarrier waves. We modify the scheme via heterodyne detection and perform security analysis for the full trusted hardware noise model in the presence of collective attacks with finite-key effects. It is shown that the system can potentially distribute the key even if the level of losses in the channel is above 9 dB. This result is consistent with the general technical level and comply with modern standards of practical CV-QKD systems. Finally, the system under consideration fully meets the criterion of composability.
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Super-resolution microscopy based on interpolation and wide spectrum de-noising
Статья научная
In the conventional single-molecule localizations and super-resolution microscopy, the pixel size of a raw image is approximately equal to the standard deviation of the point spread function. Such a raw image is referred to herein as a conventional raw image, based on which better single molecule localization effect and efficiency can be achieved. It is found that both interpolation and de-noising can effectively improve the Signal to Noise Ratio of the conventional raw image. The conventional raw image, the de-noised, the interpolated and the de-noised interpolated are compared and analyzed and compressed sensing is used for super-resolution reconstruction. The simulation results show that both the highest Signal to Noise Ratio and the best super-resolution reconstruction can be obtained by de-noising the interpolated conventional raw image. This method also renders the best super-resolution reconstruction and minimum gradient in the real experiment. De-noising the interpolated conventional raw image is an effective method to improve the super-resolution microscopy.
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Super-resolution microscopy based on wide spectrum denoising and compressed sensing
Статья научная
WSD can effectively remove random noise of a raw image from very low density to ultra-high density fluorescent molecular distribution scenarios. The size of the raw image that WSD can denoise is subject to the used measurement matrix. A large raw image must be divided into blocks so that WSD denoises each block separately. Based on traditional single-molecule localization and super-resolution reconstruction scenarios, wide spectrum denoising (WSD) for blocks of different sizes was studied. The denoising ability is related to block sizes. The general trend is when the block gets larger, the denoising effect gets worse. When the block size is equal to 10, the denoising effect is the best. Using compressed sensing, only 20 raw images are needed for reconstruction. The temporal resolution is less than half a second. The spatial resolution is also greatly improved.
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Switching median filter for suppressing multi-pixel impulse noise
Статья научная
This paper proposes a new switching median filter for suppressing multi-pixel impulse noise in X-ray images. A multi-pixel impulse is understood as a set of several neighboring pixels, the intensity of each significantly exceeds background intensity. Multi-pixel noise can occur, for example, due to the blooming effect, the reason being the limited value of pixel saturation capacity. This article defines the thresholds for the intensity increment relative to the eight immediate neighbors, above which the current pixel is processed by the median filter. The dependence of these thresholds on the number of pixels in an impulse is presented. The proposed algorithm is based on the median filtering process, which consists of several iterations. In this case, the filter has the smallest possible size, which minimizes image distortion during processing. In particular, to exclude a single-pixel impulse, pixel processing is turned on when intensity surge exceeds 3.5 with the grayscale value ranging from 0 to 1. At the same time, to exclude nine-pixel impulses, three iterations are required with the following thresholds: the first iteration with a threshold 2.0; the second iteration also with a threshold 2.0 and the third iteration with a threshold 3.5. The algorithm proposed was tested on real X-ray images corrupted by multi-pixel impulse noise. The algorithm is not only simple, but also reliable and suitable for real-time implementation and application. The efficiency of the technique is shown in comparison with other known filtering methods with respect to the degree of noise suppression. The main result of the testing is that only the proposed method allows excluding multi-pixel noise. Other advantage of the algorithm is its weak effect on the level of Gaussian noise leading to the absence of image blurring (or preserving image details) during processing.
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Статья научная
We discuss a synthesis of stochastic algorithms, obtaining expressions for gradients of Shannon, Renyi and Tsallis mutual information on the basis of the mathematical apparatus of stochastic gradient adaptation of algorithms for estimating image registration parameters. To obtain the expressions, derivatives of the image entropy with respect to the estimated parameters are used. The entropies are calculated using a Parzen window method. A comparative study of the synthesized algorithms in terms of stability and accuracy of the registration parameter estimates, including in conditions of additive noise, is carried out.
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