Статьи журнала - Компьютерная оптика
Все статьи: 2572
Статья научная
The response of fiber specklegram sensors (FSSs) is given as function of variations in the intensity distribution of the modal interference pattern or speckle pattern induced by external disturbances. In the present work, the behavior of a FSS sensing scheme under thermal perturbations is studied by means of computational simulations of the speckle patterns. These simulations are generated by applying the finite element method (FEM) to the modal interference in optical fibers as a function of the thermal disturbance and the length of the sensing zone. A correlation analysis is per-formed on the images generated in the simulations to evaluate the dependence between the changes in the speckle pattern grains and the intensity of the applied disturbance. The numerical simulation shows how the building characteristic of the length of sensing zone, combined with image processing, can be manipulated to control the metrological performance of the sensors.
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Numerically focused optical coherence microscopy with structured illumination aperture
Статья научная
In optical coherence microscopy (OCM) with a given numerical aperture ( NA ) of the objectives the transverse resolution can be increased by increasing the numerical aperture of illumination ( NAi ). However, this may also lead to attenuation of the signal with defocus preventing the effective numerically focused 3D imaging of the required sample volume. This paper presents an approach to structuring the illumination aperture, which allows combining the advantages of increased transverse resolution (peculiar to high NAi ) with small attenuation of the signal with defocus (peculiar to low NAi ) for high-resolution numerically focused 3D imaging in OCM.
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On chip optical neural networks based on mmi microring resonators for image classification
Статья научная
We propose a new on-chip optical neural network (OONN) based on multimode interference-microring resonators (MMI-RRs). The suggested structure eliminates the need for wavelength division multiplexers (WDM) to create an optical neuron on a single chip. New microring resonator structure based on 4×4 MMI coupler with a size of 24µm × 2900 µm is used for the basic elements of the computation matrix, as a result a higher bandwidth and free spectral range (FSR) can be achieved. The Si3N4 platform along with the graphene sheet is designed to modulate the signals and weights of the neural networks at a very high speed. The Si3N4 can provide wide range of operating wavelengths and can work directly with the wavelengths of color images. The structure's benefits include rapid computing speed, little loss, and the ability to handle both positive and negative values. The OONN has been applied to the MNIST dataset with a speed faster than 2.8 to 14x times compared with the conventional GPU methods.
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On the automation of gestalt perception in remotely sensed data
Статья научная
Gestalt perception, the laws of seeing, and perceptual grouping is rarely addressed in the con-text of remotely sensed imagery. The paper at hand reviews the corresponding state as well in ma-chine vision as in remote sensing, in particular concerning urban areas. Automatic methods can be separated into three types: 1) knowledge-based inference, which needs machine-readable knowl-edge, 2) automatic learning methods, which require labeled or un-labeled example images, and 3) perceptual grouping along the lines of the laws of seeing, which should be pre-coded and should work on any kind of imagery, but in particular on urban aerial or satellite data. Perceptual group-ing of parts into aggregates is a combinatorial problem. Exhaustive enumeration of all combina-tions is intractable. The paper at hand presents a constant-false-alarm-rate search rationale. An open problem is the choice of the extraction method for the primitive objects to start with. Here super-pixel-segmentation is used.
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One-shot learning with triplet loss for vegetation classification tasks
Статья научная
Triplet loss function is one of the options that can significantly improve the accuracy of the One-shot Learning tasks. Starting from 2015, many projects use Siamese networks and this kind of loss for face recognition and object classification. In our research, we focused on two tasks related to vegetation. The first one is plant disease detection on 25 classes of five crops (grape, cotton, wheat, cucumbers, and corn). This task is motivated because harvest losses due to diseases is a serious problem for both large farming structures and rural families. The second task is the identification of moss species (5 classes). Mosses are natural bioaccumulators of pollutants; therefore, they are used in environmental monitoring programs. The identification of moss species is an important step in the sample preprocessing. In both tasks, we used self-collected image databases. We tried several deep learning architectures and approaches. Our Siamese network architecture with a triplet loss function and MobileNetV2 as a base network showed the most impressive results in both above-mentioned tasks. The average accuracy for plant disease detection amounted to over 97.8 % and 97.6 % for moss species classification.
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Статья научная
This study considers the optoelectrical properties of thin films composed of linear carbon stabilized by gold nanoparticles. We explore the unique anisotropic behaviors exhibited by these films and their dependence on the degree of structural ordering. The fabrication process includes the use of colloidal systems, with a focus on the laser-induced fragmentation of gold nanoparticles within a carbon matrix. Our findings reveal that applying a potential difference significantly alters the absorption characteristics of the films, particularly enhancing absorption at frequencies associated with short linear chains, while also inducing a transparency effect in the visible range. The introduction of electrons into the carbon matrix is identified as a key factor influencing these optical properties, drawing parallels to existing literature on resonance pumping phenomena. Additionally, the results indicate a considerable modification of the Schottky barrier at the semiconductor-metal interface due to structural orientation. This research provides insight into the potential applications of these materials in optoelectronic devices and highlights the importance of structural characteristics in tailoring their properties.
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Optical elements based on silicon photonics
Статья научная
Silicon photonics is gaining substantial impulse because it permits optical devices to be realized inexpensively using standard semiconductor fabrication techniques and integrated with microelectronic chips. In this paper, we designed few optical elements such as optical power splitter, polarization beam splitter and Bragg grating based on silicon platform simulated using finite element method.
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Optical properties of lowest-energy carbon allotropes from first-principles calculations
Статья научная
We study optical properties of lowest-energy carbon allotropes in the infrared, visible and ultraviolet spectral ranges in the general gradient approximation of the density functional theory. In our calculations we use an all-electron approach as well as a pseudo-potential approximation. In the infrared range, complex dielectric functions, infrared and Raman spectra have been calculated using a CRYSTAL14 program. Electronic properties and energy-dependent dielectric functions in the visible and ultraviolet spectral ranges are calculated using a VASP program. We describe with good accuracy the experimentally known optical properties of a cubic diamond crystal. Using the obtained set of relevant calculation parameters, we predict the optical constants, dielectric functions and Raman spectra of the lowest-energy hypothetical carbon allotropes and lonsdaleite.
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Optical-digital system for real-time fingerprint identification
Статья научная
Performance of the optical-digital system for real-time fingerprint identification using a method of the optical construction of the direction field is reported.
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Optimal affine image normalization approach for optical character recognition
Статья
Optical character recognition (OCR) in images captured from arbitrary angles requires preliminary normalization, i.e. a geometric transformation resulting in an image as if it was captured at an angle suitable for OCR. In most cases, a surface containing characters can be considered flat, and a pinhole model can be adopted for a camera. Thus, in theory, the normalization should be projective. Usually, the camera optical axis is approximately perpendicular to the document surface, so the projective normalization can be replaced with an affine one without a significant loss of accuracy. An affine image transformation is performed significantly faster than a projective normalization, which is important for OCR on mobile devices. In this work, we propose a fast approach for image normalization. It utilizes an affine normalization instead of a projective one if there is no significant loss of accuracy. The approach is based on a proposed criterion for the normalization accuracy: root mean square (RMS) coordinate discrepancies over the region of interest (ROI). The problem of optimal affine normalization according to this criterion is considered. We have established that this unconstrained optimization is quadratic and can be reduced to a problem of fractional quadratic functions integration over the ROI. The latter was solved analytically in the case of OCR where the ROI consists of rectangles. The proposed approach is generalized for various cases when instead of the affine transform its special cases are used: scaling, translation, shearing, and their superposition, allowing the image normalization procedure to be further accelerated.
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Optimal calibration of a prism-based videoendoscopic system for precise 3D measurements
Статья научная
Modern videoendoscopes are capable of performing precise three-dimensional (3D) measurements of hard-to-reach elements. An attachable prism-based stereo adapter allows one to register images from two different viewpoints using a single sensor and apply stereoscopic methods. The key condition for achieving high measurement accuracy is the optimal choice of a mathematical model for calibration and 3D reconstruction procedures. In this paper, the conventional pinhole camera models with polynomial distortion approximation were analyzed and compared to the ray tracing model based on the vector form of Snell’s law. We, first, conducted a series of experiments using an industrial videoendoscope and utilized the criteria based on the measurement error of a segment length to evaluate the mathematical models considered. The experimental results confirmed a theoretical conclusion that the ray tracing model outperforms the pinhole models in a wide range of working distances. The results may be useful for the development of new stereoscopic measurement tools and algorithms for remote visual inspection in industrial and medical applications.
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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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