Статьи журнала - Компьютерная оптика
Все статьи: 2346
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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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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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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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
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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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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Research on robot motion control and trajectory tracking based on agricultural seeding
Статья научная
With the development of science and technology, agricultural production has been gradually industrialized, and the use of robots instead of humans for seeding is one of the agricultural industrializations. This paper studied the seeding path planning and path tracking algorithms of the seeding robot, carried out experiments, and compared the improved proportion, integral, differential (PID) algorithm with the traditional PID control algorithm. The results demonstrated that both the improved and non-improved control algorithms played a good role in tracking on the straight path, but the improved control algorithm had a better tracking effect on the turning path; the displacement deviation and angle deviation of the tracking trajectory of the improved PID algorithm were reduced faster and more stable than the traditional PID algorithm; the tracking trajectory was shorter and the operation time of the robot was less under the improved PID algorithm than the traditional one.
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Retinal biometric identification using convolutional neural network
Статья научная
Authentication is needed to enhance and protect the system from vulnerabilities or weaknesses of the system. There are still many weaknesses in the use of traditional authentication methods such as PINs or passwords, such as being hacked. New methods such as system biometrics are used to deal with this problem. Biometric characteristics using retinal identification are unique and difficult to manipulate compared to other biometric characteristics such as iris or fingerprints because they are located behind the human eye thus they are difficult to reach by normal human vision. This study uses the characteristics of the retinal fundus image blood vessels that have been segmented for its features. The dataset used is sourced from the DRIVE dataset. The preprocessing stage is used to extract its features to produce an image of retinal blood vessel segmentation. The image resulting from the segmentation is carried out with a two-dimensional image transformation such as the process of rotation, enlargement, shifting, cutting, and reversing to increase the quantity of the sample of the retinal blood vessel segmentation image. The results of the image transformation resulted in 189 images divided with the details of the ratio of 80 % or 151 images as training data and 20 % or 38 images as validation data. The process of forming this research model uses the Convolutional Neural Network method. The model built during the training consists of 10 iterations and produces a model accuracy value of 98 %. The results of the model's accuracy value are used for the process of identifying individual retinas in the retinal biometric system.
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Rice growth vegetation index 2 for improving estimation of rice plant phenology in costal ecosystems
Статья научная
Crop growth is one of the most important parameters of a crop and its knowledge before harvest is essential to help farmers, scientists, governments and agribusiness. This paper provides a novel demonstration of the use of freely available Sentinel-2 data to estimate rice crop growth in a single year. Sentinel 2 data provides frequent and consistent information to facilitate coastal monitoring from field scales. The aims of this study were to modify the rice growth vegetation index to improve rice growth phenology in the coastal areas. The rice growth vegetation index 2 is the best vegetation index, compared with 11 vegetation indices, plant height and biomass. The results demonstrate that the coefficient of rice growth vegetation index 2 was 0.83, has the highest correlation with plant height. Rice growth vegetation index 2 is more appropriate for enhancing and obtaining rice phenology information. This study analyses the best spectral vegetation indices for estimating rice growth.
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Статья научная
The use of metal 2D subwavelength structures (SWS) is a promising solution for all those applications where a selective emission from a thermal source is desirable, e.g. photovoltaic and blackbody emission. The investigation of the SWS' photonic bandgap properties is challenging, especially for the infrared and visible spectrum, where the fabrication difficulties have always represented an obstacle. In this paper, the anodization of aluminum films as a self-assembly method for the SWS fabrication is proposed. A rigorous calculation of 2D-SWS of gold having high absorptivity in the visible and low-absorptivity in the NIR, their fabrication by DC-sputtering deposition through anodic porous alumina templates, and their optical and topographic characterization are presented. In this paper, the anodization of aluminum films as a self-assembly method for the SWS fabrication is proposed.
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Road images augmentation with synthetic traffic signs using neural networks
Статья научная
Traffic sign recognition is a well-researched problem in computer vision. However, the state of the art methods works only for frequent sign classes, which are well represented in training datasets. We consider the task of rare traffic sign detection and classification. We aim to solve that problem by using synthetic training data. Such training data is obtained by embedding synthetic images of signs in the real photos. We propose three methods for making synthetic signs consistent with a scene in appearance. These methods are based on modern generative adversarial network (GAN) architectures. Our proposed methods allow realistic embedding of rare traffic sign classes that are absent in the training set. We adapt a variational autoencoder for sampling plausible locations of new traffic signs in images. We demonstrate that using a mixture of our synthetic data with real data improves the accuracy of both classifier and detector.
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