Статьи журнала - Компьютерная оптика
Все статьи: 2609
Orbital angular momentum of the spiral beams
Статья научная
At first sight, any rotation generates some angular momentum (it is true for a solid body). But these characteristics (rotation and orbital angular momentum) are rather different for optics and mechanics. In optics there are the situation when the rotation is important. On the other hand, there are the cases where the nonzero orbital angular momentum is necessary. The main goal of this article is to investigate a relationship between a rotation under propagation of spiral beam and its angular momentum. It can be done the following conclusion: there is no any relation between rotation under propagation of spiral beam and its OAM.
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P-CVD-SWIN: a parameterized neural network for image daltonization
Статья научная
Nowadays, about 8 % of men and 0.5 % of women worldwide suffer from color vision deficiency. People with color vision deficiency are mostly dichromats and closely related anomalous trichromats, and are subdivided into three types: protans, deutans, and tritans. Special image preprocessing methods referred to as daltonization techniques allow increasing the distinguishability of chromatic contrasts for people with dichromacy. State-of-the-art neural network architectures involve training separate models for each type of dichromacy, which makes such models cumbersome and inconvenient. In this paper, we propose for the first time a parameterized neural network architecture, which allows training the same neural network model for any type of dichromacy, being specified as a parameter. We named this model P-CVD-SWIN, supposing it a parametrized development of the recently suggested CVD-SWIN model. A generalization of the Vienot dichromacy simulation method was proposed for model training. Experiments have shown that the P-CVD-SWIN neural network parameterized by the type of dichromacy provides better preservation of chromatic naturalness during daltonization, compared to a combination of several CVD-SWIN models, each trained for its own type of dichromacy.
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Parallel implementation of a multi-view image segmentation algorithm using the Hough transform
Статья научная
We report on the parallel implementation of a multi-view image segmentation algorithm via segmenting the corresponding three-dimensional scene. The algorithm includes the reconstruction of a three-dimensional scene model in the form of a point cloud, and the segmentation of the resulting point cloud in three-dimensional space using the Hough space. The developed parallel algorithm was implemented on graphics processing units using CUDA technology. Experiments were performed to evaluate the speedup and efficiency of the proposed algorithm. The developed parallel program was tested on modelled scenes.
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Parallel implementation of the informative areas generation method in the spatial spectrum domain
Статья научная
This paper proposes a parallel implementation of the image informative segments extraction method. The images are segmented in the spatial spectrum domain. The median energy in each selected segment is viewed upon as an area. For purposes of time savings, a parallel implementation of the algorithm for calculating the areas is developed. The developed approach to the parallel algorithm implementation is tested on a high performance multicore computing system. The experiments have shown that the parallel implementation of the method allows us to obtain a three-fold speedup, which is a good result.
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Статья научная
The tracking-by-detection paradigm is widely used for people multi-object tracking tasks. Up to now, there exist many detectors and trackers, many evaluation benchmarks, which necessitates the use of relatively uniform estimation methods and metrics. It leads to necessity to choose better combined models of detectors and trackers. To solve this task, we developed a comprehensive performance evaluation methodology for estimation of people tracking accuracy and real-time by using different detectors and trackers. We conducted experiments by choosing the official pre-trained models of YOLOv5, YOLOv6, YOLOv7, YOLOv8 with representative BoTSORT, ByteTrack, DeepOCSORT, OCSORT, StrongSORT trackers under two benchmarks of MOT17 and MOT20. Detailed metrics in terms of error and speed such as higher order tracking accuracy and frames per second were analyzed for the combinations of detectors and trackers. It is concluded that the OCSORT+YOLOv6l model has the best comprehensive performance and the combination of OCSORT and YOLOv7 has the best average performance under MOT17 and MOT20.
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Статья научная
This study examines Probability Density Functions (PDFs) of several statistical models--Lognormal, Rayleigh, Gamma-Gamma, Nakagami-m, Rice, and Negative Exponential--in relation to irradiance under weak, moderate, and strong turbulence conditions. Each model exhibits unique characteristics crucial to Free-Space Optical (FSO) communication performance. Lognormal distribution suggests a high probability of low irradiance values, while Rayleigh and Rice show bell-shaped curves. Gamma-Gamma and Nakagami-m offer greater flexibility, displaying moderate peaks and gradual declines. Negative Exponential distribution shows a rapid decay, particularly in random scattering scenarios. Bit Error Rate (BER) performance is evaluated based on instantaneous signal-to-noise ratio (SNR(I)) for various modulation schemes. Among these, 16-Pulse Position Modulation (16-PPM) proves the most robust, followed by Binary Phase Shift Keying (BPSK) and 8-Phase Shift Keying (8-PSK), which also demonstrate strong performance. Differential Phase Shift Keying (DPSK) and 16-Quadrature Amplitude Modulation (16-QAM) offer a balance between performance and spectral efficiency, while 4-Pulse Amplitude Modulation (4-PAM) is highly sensitive to noise. The study reveals that Rayleigh and Rice distributions perform poorly in moderate and strong turbulence, while Nakagami-m and Gamma-Gamma perform better, with Gamma-Gamma excelling in weak and strong turbulence, and Nakagami-m in moderate conditions. At higher SNR(I) levels, BER performance converges across models, minimizing the impact of channel model on modulation scheme's performance.
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Phase reconstruction using a Zernike decomposition filter
Статья научная
Coherent wavefronts are analysed using a Zernike filter that decomposes the analyzed light field into a set of diffraction orders with amplitudes proportional to the circular Zernike polynomials. We also apply the algorithm to the calculation of the light field phase from measurements of the modules of decomposition coefficients. Operation of several filter are simulated.
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Point cloud registration based on global compatibility feature
Статья научная
In this paper, we present a point cloud registration method that utilizes a global point cloud compatibility feature. We introduce an evaluation technique called global compatibility, which helps distinguish between correct and incorrect feature point pairs by calculating the corresponding compatibility weights. To begin, we employ a spectral matching technique to select reliable seed points, allowing us to construct a consistent point set in the vicinity of these seed points. We then design a consistent filter to eliminate outliers from the obtained set. Our approach includes proposing optimal weight matching based on the characteristics of each compatible point set, alongside spectral matching for decomposing the constructed multiple compatible point sets. We assign smaller weights for points affected by larger noise, which aids in generating the corresponding rigid transformation. Ultimately, we select the best transformation as the final result. Notably, our method does not require retrieving all features from the entire point set, and it effectively removes discrete points, thereby constructing a more efficient and robust consistent point set. Experimental results demonstrate that our method performs very well on both indoor and outdoor datasets, as well as on datasets with low overlap.
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Polarization properties of three-dimensional electromagnetic Gaussian Schell-model sources
Статья научная
The polarization properties of the recently introduced three-dimensional electromagnetic Gaussian Schell-model sources [Opt. Lett. 42, 1792 (2017)] are examined. Both cases of uniform and non-uniform polarization are considered. The three-dimensional polarization states are characterized via the eigenvalues of a 3×3 source polarization matrix and, more specifically, via the indices of polarimetric purity. We show that the considered sources exhibit a variety of polarization states throughout their volumes conveniently controlled by several physically accessible source parameters.
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Preliminary results in investigation of diffractive high-efficiency objectives
Статья научная
It has been shown that high-efficiency diffractive objectives are an alternative to their refractive counterparts for applications requiring high precision transformation of monochromatic light (for example in interferometers). A 80 mm diameter prototype (N.A. - 0.158; design wavelength 632.8 nm) has been fabricated by direct laser writing on photoresist. It was manufactured on a polar coordinate laser writing system CLWS-300 that is able to write high precision DOEs up to a diameter of 300 mm. The blazed diffractive structures were written directly into a photoresist layer that was spinned on a high-precision substrate. The fabricated objective has a rms wavefront error of less than л/20 in single pass. The residual errors are predictable using manufacturing data that is recorded during the writing process for each element. This permits to provide each element with calibration data. Measurements of the fabricated DOEs show excellent agreement between the predicted and measured wavefront quality.
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Статья научная
Nematic liquid crystal planar and smoothly-irregular waveguide structures were studied experimentally and by the computer modeling. Two types of optical smoothly-irregular waveguide structures promising for application in telecommunications and control systems are studied by numerical simulation: liquid crystal waveguides and thin film solid generalized waveguide Lune-burg lens. Study of the behavior of these waveguide structures where liquid crystal layer can be used to control the properties of the entire device, of course, promising, especially since such devices are also able to perform various sensory functions when changing some external parameters, accompanied by a change in a number of their properties. It can be of interest to researchers not only in the field of the integrated optics but also in some others areas: nano-photonics, optofluid-ics, telecommunications, and control systems. The dependences of the attenuation coefficient (optical losses) of waveguide modes and the effective sizes (correlation radii) of quasi-stationary irregularities of the liquid-crystal layers on the linear laser radiation polarization and on the presence of pulse-periodic electric field were experimentally observed...
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Статья научная
We present a general-purpose, training-free framework for dimensionality reduction and clustering based on per–sample pseudo–Boolean polynomials (PBP). The method constructs compact, interpreTab. features without model fitting and is evaluated under a standardized protocol that compares PBP to PCA, t-SNE, and UMAP using identical inputs and metrics: clustering alignment (V-measure, Adjusted Rand Index), cluster geometry (Silhouette coefficient, Calinski–Harabasz index, Davies–Bouldin index), and supervised probes (linear separability and boundary complexity (1–NN error)). Across 11 diverse datasets spanning tabular, signal, and ecological domains, PBP leads on linear separability in 5/11 datasets and achieves lower boundary complexity in 2/11 datasets, while remaining competitive on clustering metrics. We report best-performing aggregation and sorting configurations per dataset and provide guidance on when PBP should be preferred for interpreTab. analysis and reproducible evaluation.
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Quality inspection of fertilizer granules using computer vision – a review
Статья научная
This research explores the fusion of computer vision and agricultural quality control. It investigates the efficacy of computer vision algorithms, particularly in image classification and object detection, for non-destructive assessment. These algorithms offer objective, rapid, and error-resistant analysis compared to human inspection. The study provides an extensive overview of using computer vision to evaluate grain and fertilizer granule quality, highlighting granule size’s significance. It assesses prevailing object detection methods, outlining their advantages and drawbacks. The paper identifies the prevailing trend of framing quality inspection as an image classification challenge and suggests future research directions. These involve exploring object detection, image segmentation, or hybrid models to enhance fertilizer granule quality assessment.
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RANSAC-Scaled Depth: A Dual-Teacher Framework for Metric Depth Annotation in Data-Scarce Scenarios
Статья научная
This paper addresses the problem of training metric monocular depth estimation models for specialized domains in the absence of labeled real-world data. We propose a hybrid pseudo-labeling method that combines the predictions of two models: a metric "teacher," trained on synthetic data to obtain the correct scale, and a foundational relative "teacher" for structurally accurate scene geometry and depth. The relative depth map is calibrated via a linear transformation, whose parameters are found using the outlier-robust RANSAC algorithm on a subset of "support" points. Experiments on the KITTI dataset show that the proposed approach improves the quality of the pseudo-labels, reducing the commonly used error metric AbsRel by 21.6 % compared to the baseline method. A compact "student" model trained on these labels demonstrated superiority over the baseline model, achieving a 23.8 % reduction in AbsRel and a 13.8 % reduction in RMSE log. The results confirm that the proposed method significantly improves domain adaptation from general purpose to the specific domain, allowing for the creation of high-precision metric models without the need to collect and annotate volumes of real data.
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Статья научная
In this report we describe a fast 3-color method of the measurement of temperature distributions on a surface of a heated solid using a RGB color camera with a high frame rate (100 images per second). Statistical error the RGB method is not high, and do not exceed around 5.5 % which is surprising taking in to account the number of the measurements at each pixel. Comparison of the results of the temperature measurements on a tungsten plate heated by infra-red laser radiation and conducted with this technique and those obtained with the acousto-optical tunable filter technique demonstrate that error of the temperature measured by 3-color method is only two times as high as that of the tandem acousto-optic filter technique method.
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Recognition of biosignals with nonlinear properties by approximate entropy parameters
Статья научная
More and more attention is being paid to the development of methods for the objective analysis of biosignals for computer medical systems. The search for new non-standard methods is aimed at improving the reliability of diagnostics and expanding the areas of their practical application. In this paper, methods for recognizing biomedical signals by the degree of severity of their nonlinear components are considered. An approach based on the use of approximate entropy closely related to Kolmogorov entropy ( K -entropy) is used. Its parameters can be used to detect dynamic irregularities associated with nonlinear properties of signals. The algorithm for calculating this characteristic is considered in detail. Based on model experiments, its main properties are analyzed. It is shown that the entropy of a finite sequence, calculated in accordance with a multistep procedure, can give an erroneous estimate of the degree of regularity of the signal. A procedure for correcting the approximate entropy is proposed, which expands the area of analysis of this function for estimating nonlinearity. It has been established that the transition to adjusted entropy makes it possible to increase the reliability of the detection of chaotic components. A set of entropy parameters is proposed for constructing recognition procedures. Examples of solving the problems of detecting atrial fibrillation by the parameters of the nonlinearity of the rhythmogram, as well as assessing the depth of anesthesia by the electroencephalogram (EEG) are given. Experiments conducted on real recordings of electrocardiogram (ECG) and EEG signals have shown the high efficiency of the proposed algorithms. The proposed methods and algorithms can be used in the development of systems for monitoring ECG of cardiological patients, as well as monitoring the depth of anesthesia by EEG during surgical operations.
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Renewed empirical formulas of Weibull distribution parameters estimates
Статья научная
The empirical formulas proposed in the literature for estimating the parameters of a two-parameter Weibull distribution, obtained using the equations of the moment method, are considered. It is noted that the formulas used to estimate the shape parameter take the form of various types of dependences on the coefficient of variation of the distribution. By modeling the empirical formulas selected for analysis, a comparative analysis of their errors relative to accurate numerical solutions of the moment method equations was carried out. A renewed empirical formula for the shape parameter is proposed. An approach to estimating the scale parameter is proposed, in which the empirical formula of the latter is reduced to the product of the standard deviation of the distribution by a power function of the coefficient of variation with an exponent equal to – 1.027. The results of applying the updated empirical formulas to numerical data obtained by modeling a random sample from the Weibull distribution are presented. It is shown that the accuracy of the proposed empirical formulas is quite high.
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Research on an image color restoration method for old art films
Статья научная
The preservation and restoration of old art films have certain practical value. Focusing on the color restoration of old art films, this paper introduced the same mapping loss on the basis of a cycle-consistent generative adversarial network, which enables the algorithm to capture more image details and achieve better transfer results. The old art films Roman Holiday and Tracks in the Snowy Forest were used as experimental data to verify the color restoration effect of the improved cycle-consistent generative adversarial network algorithm. It was found that compared with the generative adversarial network and cycle-consistent generative adversarial network algorithms, the improved cycle-consistent generative adversarial network algorithm was superior. It achieved a peak signal-to-noise ratio of 26.874, a structural similarity index measure of 0.665, a learned perceptual image patch similarity of 0.212, and a Frechet inception distance of 117.652 for Roman Holiday. Moreover, it achieved a peak signal-to-noise ratio of 22.794, a structural similarity index measure of 0.585, a learned perceptual image patch similarity of 0.247, and a Frechet inception distance of 119.265 for Tracks in the Snowy Forest. It also achieved better results in comparison with existing image color restoration methods. The results demonstrate the usability of the improved cycle-consistent generative adversarial network algorithm in color restoration of old art films, which can be applied in practice.
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Статья научная
The unique plateau geographical features and variable weather of Yunnan, China make transmission lines in this region more susceptible to coverage and damage by various foreign bodies compared to flat areas. The mountainous terrain also presents great challenges for inspecting and removing such objects. In order to improve the efficiency and detection accuracy of foreign body inspection of transmission lines, we propose a multi-UAV collaborative system specifically designed for the geographical characteristics of Yunnan's transmission lines in this paper. Additionally, the image data of foreign bodies was augmented, and the YOLOv7 target detection model, which offers a more balanced trade-off between precision and speed, was adopted to improve the accuracy and speed of foreign body detection.
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