Статьи журнала - Компьютерная оптика
Все статьи: 2609
Noise minimized high resolution digital holographic microscopy applied to surface topography
Статья научная
The topography of surface relief gratings was studied by digital holographic microscopy. The applicability of the method for quantitative measurements of surface microstructure at nanoscale was demonstrated. The method for wavefront reconstruction of surface relief from a digital hologram recorded in off-axis configuration was also applied. The main feature is noise filtration due to the presence of noise in the recorded intensity distribution and the use of all orders of the hologram. Reconstruction results proved a better effectiveness of our approach for topography studying of relief grating patterned on a ChG As2S3 - Se nanomultilayers in comparison with standard Fourier Transform and Atom Force Microscope methods.
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Noise reduction and mammography image segmentation optimization with novel QIMFT-SSA method
Статья научная
Breast cancer is one of the most dreaded diseases that affects women worldwide and has led to many deaths. Early detection of breast masses prolongs life expectancy in women and hence the development of an automated system for breast masses supports radiologists for accurate diagnosis. In fact, providing an optimal approach with the highest speed and more accuracy is an approach provided by computer-aided design techniques to determine the exact area of breast tumors to use a decision support management system as an assistant to physicians. This study proposes an optimal approach to noise reduction in mammographic images and to identify salt and pepper, Gaussian, Poisson and impact noises to determine the exact mass detection operation after these noise reduction. It therefore offers a method for noise reduction operations called Quantum Inverse MFT Filtering and a method for precision mass segmentation called the Optimal Social Spider Algorithm (SSA) in mammographic images. The hybrid approach called QIMFT-SSA is evaluated in terms of criteria compared to previous methods such as peak Signal-to-Noise Ratio (PSNR) and Mean-Squared Error (MSE) in noise reduction and accuracy of detection for mass area recognition. The proposed method presents more performance of noise reduction and segmentation in comparison to state-of-arts methods. supported the work.
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Статья научная
In this paper we investigate non-Markovian evolution of a two-level system (qubit) in a bosonic bath under influence of an external classical fluctuating environment. The interaction with the bath has the Lorentzian spectral density, and the fluctuating environment (stochastic field) is represented by a set of Ornstein-Uhlenbeck processes. Each of the subenvironments of the composite environment is able to induce non-Markovian dynamics of the two-level system. By means of the numerically exact method of hierarchical equations of motion, we study steady states of the two-level system, evolution of the reduced density matrix and the equilibrium emission spectra in dependence on the frequency cutoffs and the coupling strengths of the subenvironments. Additionally, we investigate the impact of the rotating wave approximation (RWA) for the interaction with the bath on accuracy of the results.
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Non-stability of MM-wave radar imaging of the car in dynamics
Статья научная
One of the important requirement to the radioimages formed by the systems of the automatic vehicle classification and identification or automobile imaging radar is the quality of forming radioimages. In ideals the quality of radioimages can be equal to optical images, because car radar must not only to determinate availability of the obstacle, but to recognized and identificated it too. The conducted theoretical and first experimental investigations have shown that the radar images of obstacles formed by radar are characterized by the non-stability of the radioimages, which can not permit to identificated and recognized the targets. Unsteadies of the car radar imaging in dynamics are analyzing and discussed in this paper. The methods of the decreasing of the radar imaging unsteadies are discussed.
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Novel approach of simplification detected contours on X-ray medical images
Статья научная
This paper gives description of a method for simplifying the number of points representing detected contours of the bones on digital X-ray images. Such simplification permits simplify way for correction the location of these points in the cases, if the analyzed image has poor quality, and to reduces the time of analysis it to get the reference lines and angles for diagnosis purposes of the area under investigation.
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Novel zoning rule for designing square Fresnel zone plate
Статья научная
An improved zoning rule is presented for designing a square Fresnel zone plate lens (FZPL). This new rule results in a higher gain when the FZPL is used as an antenna element or can enhance the focusing properties of the square FZPL when used to collimate an incident plane wave. The derivation of this improved zoning rule is presented along with simulated results for some typical cases.
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Numerical approach to compound quantum repeater scheme with coherent states
Статья научная
A numerical model of a quantum repeater operating with Schrödinger cat states is constructed. The model describes the performance of such a system in the presence of decoherence effects, namely, noise in the quantum channel and the efficiency of the photon-number-resolving detector. In the framework of the numerical model, a theoretical analysis of the system functioning is carried out for the elementary link by calculating its performance characteristics. Namely, we calculate photodetector click probabilities and fidelity for various sets of decoherence parameters. These estimates are necessary in the context of further experimental research at the junction with other branches of quantum communications, so that to use the entanglement distribution when it comes to operating quantum teleportation and quantum key distribution protocols based on entanglement. The model will be developed further as a versatile drag-and-drop software simulating the full-fledged entanglement swapping protocol operation.
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Numerical simulation of 2D electrodynamic problems with unstructured triangular meshes
Статья научная
We present a generalization of standard leap-frog plus Yee mesh approach for Cauchy problem in electrodynamics simulations on unstructured triangulated mesh. The presented approach still inherits from finite-difference time-domain and do not use techniques developed in finite-volume time-domain approach. In the paper the whole flow from mesh creation to actual simulation is presented. The proposed computation flow is parallel ready and can be implemented for distributed systems (computation servers, graphical processing units, etc.). We studied the influence of non-regular triangulation on stability and dispersion properties of numerical solution.
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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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Статья научная
This research addresses the problem of automatic object detection in images under limited-visibility conditions, where objects are partially occluded, the background is complex, and lighting and viewpoints vary widely. The proposed approach combines pretraining on a programmatically generated synthetic dataset of 18,000 images - produced using the Visualization Toolkit (VTK) library - with fine-tuning on a compact real-image dataset of 2,000 annotated photographs (500 per class). Six deep neural network architectures - Faster R-CNN ResNet-50 FPN, SSD MobileNet V3, YOLOv11n, EfficientDet-D7, DETR-DC5, and CenterNet- were evaluated across three training regimes: synthetic-only, real-only, and combined (90% synthetic / 10% real). Hybrid training yielded the most substantial improvements: YOLOv11n achieved mAP@0.5 = 0.91 and mAP@0.75 = 0.86 (Precision = 0.89, Recall = 0.90, F1 = 0.89, 82 FPS), compared to 0.79 (synthetic-only) and 0.78 (real-only), representing a gain of up to +15 percentage points in mAP@0.5. EfficientDet-D7 reached mAP@0.5 = 0.87 and mAP@0.75 = 0.81, while CenterNet achieved mAP@0.5 = 0.88 at 35 FPS. Robustness analysis under simulated occlusion demonstrated that hybrid-trained models maintain reliable detection even under severe conditions: YOLOv11n retained mAP@0.5 = 0.78 at 50% occlusion and mAP@0.5 = 0.65 at 25% object visibility, while the degradation in mAP under 75% occlusion did not exceed 20% of the baseline level. The results confirm the viability of synthetic data as a standalone pretraining resource and validate the proposed hybrid pipeline for applications in autonomous driving, video surveillance, and industrial inspection.
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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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