Image System Research Articles

E. Boratynsky’s poem ‘The Stillborn’ [‘Nedonosok’] in the context of Slavic mythology

The article deals with E. Boratynsky’s poem about a spirit of a nonviable nedonosok, or stillborn, drifting between heaven and earth. Scholars have noted the poem’s affinity with works of Dante and Goethe, as well as Plato’s philosophy and the Old Testament. The present study considers the poem’s system of motifs and images in comparison with concepts found in folklore and mythology. The East Slavs believed premature or stillborn babies to be dangerous creatures. They emerged from the ‘other world’ and were ‘unclean.’ For that reason, an infant’s christening was a crucial means to humanize the baby. Unbaptized children (preterm or stillborn) were trapped in the air between heaven and earth. They were feared along with the rest of ‘unclean forces,’ e. g., spirits of sorcerers and sinners. Barred from entering heaven and restless, their existence was an agony that made others suffer as well. Boratynsky poetically interprets a popular superstition about a ‘wrongful’ or ‘bad’ death and its consequences for an infant who was forced out of this world unbaptized. These archaic topics and imagery, among others, inspired the poet’s religious and philosophical reflections.

Enhancing the security of image communication with a new hyper-chaotic system

The rapid expansion of multimedia communication necessitates the development of advanced and resilient cryptographic systems. As computational power grows, traditional encryption methods become susceptible to brute-force attacks. Cybersecurity threats are in a constant state of flux, requiring the creation of innovative cryptographic systems to outpace these developments. Chaotic systems offer a very good promise in cryptography as they are sensitive to initial conditions and parameters. In this study, the authors propose a novel hypercryptographic system (referred as NHCS) for color images that integrates a new hyperchaotic system with the RSA algorithm. This approach combines the unpredictable behavior of the hyper-chaotic system with the robust encryption capabilities of the RSA algorithm. This combination provides an additional layer of security. The hyper-chaotic systems offer a broader range of parameter values leading to chaos. Moreover, due to their four-dimensional nature, they can be employed to encrypt four-color channels. The NHCS algorithm has a large key space (of size 2704), 1024-bit RSA encrypted for higher security. The key sensitivity of this algorithm is of the order 10−16. The effectiveness of NHCS is validated through numerous test images from the USC-SIPI database and is bolstered by statistical analysis. The two indicators NPCR (∽100% ) and UACI (>33%) ensure that the system is robust against differential attacks. We perform a correlation analysis of the images and observe that correlation coefficients between adjacent pixels of the encrypted images are close to zero. Further, the information entropy values of the encrypted images are close to the ideal value 8. PSNR, MSE, and other statistical measures are found near their respective ideal values. A comparison with the other methods shows that NHCS is very promising.

Definition of a coordinate system for multi-modal images of the temporal bone and inner ear.

The position and orientation of the head is maintained to be relatively similar during the CT / MR imaging process. However, the position / orientation dissimilarities present in the resulting images between patients, or between different scans of the same patient, do not allow for direct comparison of the images themselves or features / metrics extracted from them. This paper introduces a method of defining a coordinate system which is consistent between patients and modalities (CT and MR) for images of the temporal bone, using easily identifiable landmarks within the semicircular canals. Cone Beam CT and high resolution MRI (T2) images of the temporal bone from 20 patients with no cochlear or temporal bone pathology in either modality were obtained. Four landmarks within the semicircular canals were defined that can be identified in both modalities. A coordinate system was defined using these landmarks. Reproducibility of landmark selection was assessed using intra- and inter-rater reliability (for three expert raters and two repeats of the landmark selection). Accuracy of the coordinate system was determined by comparing the coordinates of two additional landmarks in CT and MR images after their conversion to the proposed coordinate system. Intraclass Correlation Coefficients at a 95% level of confidence showed significant agreement within and between raters as well as between modalities. The differences between selections, raters, and modalities (as measured using mean, standard deviation, and maximum) were low and acceptable for clinical applications. The proposed coordinate system is suited for use in images of the temporal bone and inner ear. Its multi-modal nature enables the coordinate system to be used in tasks such as image co-registration.

Empirical methods for recognizing and evaluating cultural heritage value of Timber-Arched Lounge Bridge from the perspective of cultural memory

ABSTRACT The objective of this research is to formulate a pathway for the revitalization and preservation of cultural heritage, offering empirical methodologies for the recognition and assessment of cultural heritage values, with the ultimate goal of facilitating the dynamic conservation of Timber-Arched Lounge Bridge cultural heritage. Hence, the present research has developed an approach called the activation protection path method for comprehending, evaluating, and revitalizing the invaluable aspects of vernacular cultural heritage. To begin with, by employing the lens of Cultural Memory Theory and leveraging its holistic approach, the significance of Timber-Arched Lounge Bridges as a cultural heritage site is examined. Furthermore, an elaborate index system is devised to facilitate the assessment of its value. Secondly, an evaluation model was constructed to assess the cultural heritage value of the Timber-Arched Lounge Bridge. This paper explores the influencing factors of cultural heritage value as the research basis for the cultural heritage revitalization and protection work of Timber-Arched Lounge Bridge. Based on the case study of 19 preservation units of Timber-Arched Lounge Bridges in Shouning County, Fujian Province, the findings can be concluded as follows: 1). Cultural Heritage Value: The cultural heritage value of Timber-Arched Lounge Bridge in Shouning County is estimated to be approximately 178.45 million yuan. Among the different systems, the Text system accounts for 16%, the Image system accounts for 44%, and the Ritual system accounts for 40%. 2). Activation Investment Ratio: Based on the evaluation results of each index value of Timber-Arched Lounge Bridge cultural heritage, this study establishes the capital investment ratio for activating the heritage. This ratio provides guidance for successfully implementing the practical path of activating and protecting the cultural heritage of Timber-Arched Lounge Bridge. Through an in-depth analysis of the heritage value of Timber-Arched Lounge Bridge and the establishment of an evaluation model, this study lays the foundation for activating and preserving vernacular cultural heritage. By promoting the construction of the value subject’s identity, this research contributes to guiding the practical path of activating and protecting the living heritage of Timber-Arched Lounge Bridges.

Optimization of Sparse Camera Array Arrangement using Grid-based Method

—This study explores the application of multi-camera array technology in super-resolution (SR) imaging system. We propose an innovative method based on grid representation to optimize camera arrangements using sparse Gaussian processes and variational inference. This approach significantly enhances the image reconstruction quality of sparse camera arrays. Unlike conventional techniques that provide only qualitative conclusions, our grid-based method precisely optimizes camera positions and effectively simulates the impact of assembly errors. The optimized camera arrangement substantially improves the SR reconstruction quality of sparse array imaging systems, reducing contour jaggedness and high-frequency aliasing. Extensive simulations and experimental validations confirm the robustness and practical applicability of our method. The results demonstrate that the optimized camera arrangements can achieve high-resolution imaging with enhanced robustness against assembly errors, indicating their potential for various applications such as biological microscopy, remote sensing, and smartphone photography. This work presents a new and effective strategy for designing sparse camera array imaging systems, offering significant improvements in both image quality and system reliability.

Retraction Note: Light image enhancement based on embedded image system application in animated character images

Retraction Note: Light image enhancement based on embedded image system application in animated character images

Retraction Note: Application of cloud computing image system based on optical communication in museum VR design

Retraction Note: Application of cloud computing image system based on optical communication in museum VR design

A Segmentation-Based Automated Corneal Ulcer Grading System for Ocular Staining Images Using Deep Learning and Hough Circle Transform

Corneal ulcer is a prevalent ocular condition that requires ophthalmologists to diagnose, assess, and monitor symptoms. During examination, ophthalmologists must identify the corneal ulcer area and evaluate its severity by manually comparing ocular staining images with severity indices. However, manual assessment is time-consuming and may provide inconsistent results. Variations can occur with repeated evaluations of the same images or with grading among different evaluators. To address this problem, we propose an automated corneal ulcer grading system for ocular staining images based on deep learning techniques and the Hough Circle Transform. The algorithm is structured into two components for cornea segmentation and corneal ulcer segmentation. Initially, we apply a deep learning method combined with the Hough Circle Transform to segment cornea areas. Subsequently, we develop the corneal ulcer segmentation model using deep learning methods. In this phase, the predicted cornea areas are utilized as masks for training the corneal ulcer segmentation models during the learning phase. Finally, this algorithm uses the results from these two components to determine two outputs: (1) the percentage of the ulcerated area on the cornea, and (2) the severity degree of the corneal ulcer based on the Type–Grade (TG) grading standard. These methodologies aim to enhance diagnostic efficiency across two key aspects: (1) ensuring consistency by delivering uniform and dependable results, and (2) enhancing robustness by effectively handling variations in eye size. In this research, our proposed method is evaluated using the SUSTech-SYSU public dataset, achieving an Intersection over Union of 89.23% for cornea segmentation and 82.94% for corneal ulcer segmentation, along with a Mean Absolute Error of 2.51% for determining the percentage of the ulcerated area on the cornea and an Accuracy of 86.15% for severity grading.

Тирсо де Молина: маньеризм на пороге барокко

Continuing the study into the creative work of the Spanish playwright Tirso de Molina, in this article the author focuses on the problems of the writer’s works on the borderline between Mannerism and the Baroque that pose the most important questions of human existence, relations with the world and with God. In a broad historical, cultural, philosophical and religious context, the article analyses autos and ‘dramas about saints’, as well as the two masterpieces by Tirso de Molina — The Man Condemned for Lack of Faith and The Trickster of Seville, or the Stone Guest. In the drama The Man Condemned for Lack of Faith, the traditional image of a Christian righteous is debunked and the exaltation of a sinner is justified. In The Trickster of Seville, or the Stone Guest, criticism of morals is closely intertwined with mythopoetic imagery, and the tragic — with the grotesque, marking the tragicomic decline of the Renaissance and the transition from Mannerism to the problems of the Baroque. The optimistic anthropocentrism of the Renaissance is shifting towards the dynamics and tragedy of being and the heightened emotionality and polarity of the image system.

Grating-based spatial harmonic frequency X-ray imaging for qualitative and quantitative studies of granular and liquids materials

Grating-based spatial harmonic frequency X-ray imaging method allows the individual reconstruction of attenuation, scattering and phase-contrast X-ray images with a single exposure of the samples. In this work, the influence of the attenuation grating features (visibility and projected period) and sample features (thickness and grains sizes) on the reconstructed images were experimentally explored. Results showed that fringe visibility higher than 15% are fundamental for the proper image reconstruction. Even though reconstructed imagens are low spatial resolution (140–340 μm), they presented higher signal-to-noise ratio (SNR 85–700) than conventional images (SNR 14–39), due to the Fourier analyses procedure. Scattering could not resolve the individual grains structures, nevertheless, they revealed the presence of structures smaller than the image system resolution. Finally, it is presented that combining attenuation and scattering signals allows differentiation among the different grain sizes in granular materials and different liquids that appears similar in conventional images.

Effects of CO2 dilution on ignition characteristics in lean premixed H2/Air flames

The research has examined the effects of CO2 dilution on ignition characteristics in H2/air mixtures. An ignition kernel was initiated by a laser-induced plasma in H2/air/CO2 mixtures with a bulk velocity of 6.5 m/s. An infrared camera was used to measure radiation intensity emitted from H2O and ignition probabilities. A high-speed schlieren image system was utilized to measure ignition kernel areas and ignition time. High-speed chemiluminescence was performed to examine OH* intensities. Numerical simulations were conducted using GRI 3.0 mechanisms to calculate reaction rates and laminar flame speeds. The ignition probability is highest for the undiluted mixtures and decreases with increasing the CO2 dilution fraction at constant adiabatic temperatures. A prolonged ignition time is observed at elevated CO2 dilution concentrations. Increasing the CO2 mole fraction decreases the ignition kernel growth, the integrated OH* intensity, and the integrated radiation intensity for each adiabatic temperature. CO2 reacts with H radicals and decreases the production of OH*, OH, and H2O. The CO2 dilution in the H2/air flames significantly contributes to the reduced reaction rate and flame speed, resulting in the low ignition probability. The high ignition probability is found at the large integrated OH* intensity in all cases. The ignition probability is high at the large integrated radiation intensity under the constant adiabatic flame temperatures. The OH* intensity is a critical parameter to estimate the ignition probability in the diluted lean hydrogen flames.

Tree species classification based on PointNet++ deep learning and true- colour point cloud

ABSTRACT Accurate identification of tree species is the foundation of forest resource surveys and an important research field in forestry remote sensing. The introduction of the PointNet++ deep learning network to point cloud processing provides a new approach for tree species identification. This network can directly compute and train unordered point clouds, greatly reducing the manual selection and extraction process of feature data. However, how to establish a high-quality single tree point cloud dataset is a key issue to be solved. In this study, a 2.5-ha temperate coniferous broad-leaved mixed forest located in Mao’er Mountain Experimental Forest Farm in Heilongjiang Province, China, was investigated. The unmanned aerial vehicle (UAV) RGB image and LiDAR synchronous observation system were used to obtain the true-colour point clouds of the forest. Combining upsampling and downsampling methods, a dataset containing coordinates, normal vectors, RGB, and intensity information was constructed from the original point cloud. Comparative experiments were designed based on resampling algorithms, number of sampling points, feature information, and time cost to find the optimal feature information and processing methods for tree species classification. The results showed that the accuracy of tree species classification by using PointNet++ was greatly improved after adding RGB and point cloud intensity information. The classification accuracy was about 5% higher than that using only coordinate data sets. In addition, the combination of PU-Net downsampling network based on point cloud completion and geometric upsampling method achieved the highest classification accuracy (OA = 0.944) when the number of single trees point cloud was 3072. The algorithm also took a relatively shorter running time. This study demonstrated that the introduction of multi-feature information and the optimization of resampling method can provide new solutions for tree species classification based on the PointNet++ deep learning network.

An improved reversible watermarking scheme using embedding optimization and quaternion moments

Digital watermarking of images is an essential method for copyright protection and image security. This paper presents an innovative, robust watermarking system for color images based on moment and wavelet transformations, algebraic decompositions, and chaotic systems. First, we extended classical Charlier moments to quaternary Charlier moments (QCM) using quaternion algebra. This approach eliminates the need to decompose color images before applying the discrete wavelet transform (DWT), reducing the computational load. Next, we decompose the resulting DWT matrix using QR and singular value decomposition (SVD). To enhance the system's security and robustness, we introduce a modified version of Henon's 2D chaotic map. Finally, we integrate the arithmetic optimization algorithm to ensure dynamic and adaptive watermark insertion. Our experimental results demonstrate that our approach outperforms current color image watermarking methods in security, storage capacity, and resistance to various attacks, while maintaining a high level of invisibility.

Development of a method for differential diagnostic of a recurrent glial tumor from radiation necrosis by clinical decision support system for MRI images

Development of a method for differential diagnostic of a recurrent glial tumor from radiation necrosis by clinical decision support system for MRI images

A secure and privacy-preserving technique based on coupled chaotic system and plaintext encryption for multimodal medical images

A secure and privacy-preserving technique based on coupled chaotic system and plaintext encryption for multimodal medical images

Stray light analysis and suppression of a UV multiple sub-pupil ultra-spectral imager

A multiple sub-pupil ultra-spectral imager system for simultaneous detection of multiple substances is proposed. By employing pupil separation prisms and grating multilevel spectra, the system achieves simultaneous detection of three spectral channels with a single spectrometer and detector, featuring an ultra-high spectral resolution of 0.1 nm. However, due to simultaneous detection of three channels, the system suffers from significant stray light issues. In response to this problem, a UV multiple sub-pupil ultra-spectral imager system optical-machinery model is constructed in this article. The main sources of stray light are determined through theoretical derivation and simulation analysis, and the level of stray light in the system is analyzed using simulation analysis software. A structure for stray light suppression is optimized, and the use of multispectral filters is proposed to suppress stray light generated by spectral crosstalk in the system. The effectiveness of stray light suppression is evaluated based on the energy response of the receiving surface. The analysis results show that after optimization, the level of stray light in the T1 channel is reduced from 1.4% to 0.65‰, in the T2 channel from 3.0‰ to 0.5‰, and in the T3 channel from 0.16‰ to 0.05‰. Therefore, it can be concluded that the proposed method for stray light suppression in the UV multiple sub-pupil ultra-spectral imager system addressed in this article meets the indicator requirements.

Turbulent Image Restoration in Atmosphere with Cyclopean Processing via Binocular Fusion

Abstract The outstanding issue to overcoming atmospheric turbulence on distant imaging is a fundamental interest and technological challenge. We propose a novel scenario and technique to restore the optical image in turbulent environmental by referring to Cyclopean image with binocular vision. With human visual intelligence, image distortion resulting from the turbulence is shown to be substantially suppressed. Numerical simulation results taking into account of the atmospheric turbulence, optical image system, image sensors, display and binocular vision perception are presented to demonstrate the robustness of the image restoration, which is compared with a single channel planar optical imaging and sensing. Experiment involving binocular telescope, image recording and the stereo-image display is conducted and good agreement is obtained between the simulation with perceptive experience. A natural extension of the scenario is to enhance the capability of anti-vibration or anti-shaking for general optical imaging with Cyclopean image.

Сюжетные коллизии детективного романа Ахмета Умита «Народ» (2006)

This article is devoted to the structural and substantive analysis of one of the most famous detective novels by the popular Turkish writer Ahmet Umit "The People" (2006), which stands somewhat apart in the mainstream of his work. The article shows that, unlike other detective stories by the author, the action immediately begins with a crime, and as the plot develops, more and more murders enter the narrative orbit. In parallel with the detective line, the novel develops the idea of multiculturalism in Turkey, in which different peoples and religions have long lived in peace and harmony (Christians, Muslims, Jews). Hence the title of the novel, which is not about some specific people, but about peoples historically coexisting within the framework of a single Turkish state. The purpose of the study is to substantiate that this novel fits into the writer's detective paradigm from the point of view of poetological features. The article analyzes the plot and compositional features of the novel with an emphasis on plot collisions and the image system. The scientific novelty of the study lies in the fact that the novel in question "Umita" for the first time becomes an object of analytical study in the domestic Turkological literary criticism. For the first time, the problems of the novel are considered through the prism of its structural and meaningful content. For the first time, it is proved that the artistic structure of the novel is somewhat unusually constructed for the author's detective paradigm. As a result, it is proved that the poetics and plot of the novel correlate with the historical detective genre developed by A. Umit in its most diverse variants.

The visual image system of the city of Saratov

The visual image system of the city of Saratov

Assessment of comprehensive PAH index in roasted Tan lamb by two-dimensional correlation spectroscopy combined with hyperspectral imaging.

Thermally processed meat may contain harmful compounds, including polycyclic aromatic hydrocarbons (PAHs). This study constructed, for the first time, the comprehensive PAH index (CPI) concentration (phenanthrene [26.47%], acenaphthene [21.83%], pyrene [18.64%], fluoranthene [17.11%], fluorene [8.49%], and anthracene [7.46%]). A visible near-infrared (Vis-NIR) hyperspectral image (HSI) system was employed to detect CPI in 150 roasted Tan lamb samples. Furthermore, two-dimensional correlation spectra were used to identify spectral features and reveal the order of chemical bond changes under the characteristic peaks at 579-737-631-449nm. The results indicated that competitive adaptive reweighted sampling-multiple linear regression quantitative prediction model worked the best with calibration set coefficient of determination of 0.9161, calibration set coefficient of root mean square error of 2.3426µg/kg, R-squared prediction of 0.8469, and root mean square error of prediction of 2.4119µg/kg. Finally, PAH content distributions were visualized using the best prediction model. This study aimed to propose a feasible method for CPI in roasted Tan lamb detection based on Vis-NIR HSI coupled with multivariate analysis methods.