Night Vision Research Articles

GHE-Ensemble: Enhanced Hybrid Image Enhancement Model for Night Vision Multi-Object detection in Autonomous Vehicle

Autonomous vehicle is the exponential growing topic in the research filed due its huge demand in the current industry. Where object detection plays the major role to take any major decision. Object detection in the normal vision yields the excellent performance due to deep learning models. But object detection in the night vision does not yield the good performance due to various challenges in it. In the proposed work created a night vision database called BDD-Darko where it contains night vision images with multi objects. Applied novel GHE-Ensemble model for image enhancement technique and trained using deep learning model Yolov5 for the multi-object detection in the night vision. Which resulted in 65.3 % accuracy. Proposed model is yielding better results for image enhancement technique for night vision than the previous existing model and detecting the multi object in the single frame with better performance. This paper proposes (1)A new database called as BDD-Darko which contains night vision image with multiple objects. (2) A Novel GHE-Ensemble model for image enhancement technique for night vision images

Effect of the chromaticity of stimuli on night vision disturbances

The perception of halos and other night vision disturbances is a common complaint in clinical practice. Such visual disturbances must be assessed in order to fully characterize each patient’s visual performance, which is particularly relevant when carrying out a range of daily tasks. Visual problems are usually assessed using achromatic stimuli, yet the stimuli encountered in daily life have very different chromaticities. Hence, it is important to assess the effect of the chromaticity of visual stimuli on night vision disturbances. The aim of this work is to study the influence of the chromaticity of different visual stimuli on night vision disturbances by analyzing straylight and visual discrimination under low-light conditions. For that, we assessed the monocular and binocular visual discrimination of 27 subjects under low illumination using the Halo test. The subjects’ visual discrimination was assessed after exposure to different visual stimuli: achromatic, red, green, and blue, both at the monitor’s maximum luminance and maintaining the same luminance value for the different visual stimuli. Monocular straylight was also measured for an achromatic, red, green, and blue stimuli. The blue stimulus had the greatest effect on halos in both monocular and binocular conditions. Visual discrimination was similar for the red, green, and achromatic stimuli, but worsened at lower luminance. The greatest influence of straylight was observed for the blue stimulus. In addition, visual discrimination correlated with straylight measurements for achromatic stimuli, wherein greater straylight values correlated with an increased perception of halos and other visual disturbances.

High‐efficiency and ultracompact pancake optics for virtual reality

AbstractPancake lens has been widely used in virtual reality (VR) and mixed reality (MR) due to its compact form factor. However, using a half mirror (HM) to fold the optical path results in a tremendous optical loss. To enhance the optical efficiency while keeping a compact form factor, we present a new folded optical system incorporating a nonreciprocal polarization rotator. In our proof‐of‐concept experiment using a commercial Faraday rotator (FR), the theoretically predicted 100% efficiency is validated. Besides, the angular response of terbium gallium garnet (TGG) material is simulated for the first time and the results indicate that such an FR is relatively insensitive to the incident angle, which can dramatically enhance the contrast ratio of our pancake design. Finally, the potential application of such pancake optics for ultracompact near‐infrared (NIR) night vision goggles is also discussed.

A Rare Case Report of Bardet–Biedl Syndrome: A Syndrome of Pentad Symptoms

Bardet–Biedl syndrome (BBS) is a clinically and genetically heterogeneous disorder that manifests as a result of primary cilia impairment, characterized by retinitis pigmentosa, obesity, mental retardation, hypogonadism, and polydactyly. The five findings together are called “the pentad” and are found in most of the cases. This is the case of a 14-year-old boy, 2nd issue of consanguineous marriage of his parents, having a positive family history, who presented with progressive dimness of vision, learning disability, increased hunger, and weight since childhood. Initially, there were impaired night vision and peripheral vision problems, and later loss of color vision. He had no hearing problem, anosmia, cold intolerance, or steroid-taking history. His intranatal and postnatal history was uneventful except slightly delayed developmental milestone. His body mass index was 32.7 kg/m2, waist–hip ratio was 1.08, height was in the 50th centile on the growth chart. He had polydactyly, high-arched palate, acanthosis nigricans, and buried penis; testicular volume was prepubertal. Laboratory findings revealed high triglyceride, impaired glucose tolerance, hypogonadotropic hypogonadism, and grade-III fatty liver. He had bony spicule-like pigmentation in the periphery of both eyes suggestive of retinitis pigmentosa. Based on these data, BBS was diagnosed. In conclusion, BBS is a rare clinical syndrome that may go unnoticed by many clinicians. Renal failure is the leading cause of morbidity and mortality in patients with BBS. Therefore, early detection of BBS is vital to halt the progression of renal impairment.

Macula Lesions in Retinitis Pigmentosa

Aim: To describe the pattern of macula lesions in patients with retinitis pigmentosa attending a Retina outpatient clinic in Ibadan, Nigeria. Methodology: A retrospective review of patients with retinitis pigmentosa seen at the Retina clinic of the University College Hospital, Ibadan, Nigeria between May 2018 and June 2022. Data analysis was by SPSS (version 23) and statistical significance was placed at p < 0.05. Results: Forty-six (2.4%) of 1911 patients seen at the retina clinic during the study period had a diagnosis of retinitis pigmentosa. There were 24 (55.8%) males and 19 (44.2%) females. The mean age was 39.4 ± 19.2 years (range of 9 to 78 years). Eighty-six percent of patients were of the Yoruba ethnic group. The most common ocular complaint was poor vision which was present in forty patients (93.0%), followed by poor night vision in 26 (74.3%) patients and loss of peripheral vision in 11 (47.8%) patients. Visual impairment was present in 72.2% of patients. Maculopathy accounted for 61.3 percent of patients with visual impairment. Fifty-three (68.9%) eyes had macula lesions. This accounted for 62. 8% of all patients with RP. The macula lesions include atrophic maculopathy, cystoid macula oedema and epiretinal membrane. Atrophic maculopathy was the most common maculopathy. Coexisting ocular morbidities such as cataract dominantly of the posterior subcapsular morphology was present in 33 (42.3%) eyes while glaucoma was present in two eyes of a single patient. Conclusion: Macula lesions in retinitis pigmentosa may be a main cause of visual impairment in this population. Atrophic maculopathy is the most prevalent macula lesion associated with RP in this study.

Night Time Car Accident Prevention with AI Vision

Abstract: Night vision object detection with computer vision performs a vital function in diverse fields, when its dark, regular computer vision has trouble seeing things clearly. But because of new technology, we can now detect objects better in the dark. Our approach uses advanced learning methods and special sensors to help us see in darkness. By improving images, picking out important details, and using strong computer programs, we can spot objects accurately. After lots of testing, we've found our system works really well, with few mistakes and it's fast too. It's useful in surveillance, self-driving cars, security, and rescue missions, making dark places safer. So, basically, our system is like giving night vision to computers. It's like putting on special glasses that help you see in the dark. With this technology, we can keep an eye on things even when it's hard to see, whether it's for keeping people safe or making sure our cars can drive themselves without crashing.

Boosting Near‐Infrared Emission in Spinel‐Type Phosphor via Oxygen Vacancy Engineering for Versatile Application

AbstractFe3+‐doped MgGa2O4 (MGO: Fe3+) spinel‐type near‐infrared (NIR) phosphor with non‐toxicity, outstanding thermal stability, and tunable emission has recently gained great concern owing to its wide applications. Nevertheless, the existence of detrimental O defects in the MgGa2O4 host and the forbidden d‐d transitions of Fe3+ lead to unsatisfactory luminescence efficiency, limiting the commercial application. In this study, a vacancy repairing engineering has been innovatively developed via F− substitution in MGO: Fe3+ (MGOF: Fe3+) for significantly enhancing NIR emission and maintaining outstanding thermal stability. Specifically, F− substitution with a similar radius effectively repairs the intrinsic O vacancy defects of MGO, thereby prohibiting the detrimental electron‐capturing effect. Meanwhile, F− incorporation can make the lattice of MGO distort and break the forbidden transition of Fe3+. Significantly, the obtained MGOF: Fe3+ presents a 16‐fold higher emission intensity than that of MGO: Fe3+. More important, the MGOF: Fe3+ can remain at 91.17% (363 K) and 85.10% (423 K). Finally, the NIR emission of MGOF: Fe3+ can be used for night vision, non‐destructive biological tissue detection, and food analysis. The proposed vacancy repairing strategy can certainly stimulate some new thoughts and concepts in designing high‐performance phosphors for wider applications.

Bringing vision to climate: A hierarchical model for water depth monitoring in headwater streams

Stream-observing cameras have recently been deployed in stream systems to monitor water depth dynamics. However, most existing image-based water depth monitoring methods require additional gauging equipment, extensive manual annotations, or complex manual calibration. In this paper, we propose the hierarchical model, a novel multi-modal and multi-scale deep learning framework for monitoring water depth in headwater streams with only a field camera capable of night vision and no additional equipment. In particular, the hierarchical model integrates long-term dynamic patterns extracted from large-scale meteorological data with short-term dynamic patterns extracted from small-scale stream image data to jointly monitor water depth at a fine-level temporal resolution. In order to overcome the issue of limited availability of images, we introduce a transfer learning strategy and incorporate more accurate long-term patterns that enable the hierarchical model to perform competitively even with a small number of images. We evaluate our method on a real-world headwater stream monitoring dataset from the West Brook study area in western Massachusetts, United States. Our extensive experiments demonstrate that the hierarchical model outperforms several state-of-the-art methods for water depth monitoring, and that more accurate long-term patterns can better guide the monitoring of short-term patterns with excellent flexibility and less computational cost. The mean absolute error of our hierarchical model achieves a remarkable level of 4.9cm at the study site with 0.89m average water depths, and only 12.5cm at more drastically varied site with 3.95m average depths.

Survival, Sustenance, and Self-Sufficiency in a Tale of Two Sisters: Plant Geographies in Jean Hegland’s "Into the Forest"

As evidenced by its title, Into the Forest (1996) by Jean Hegland traces the movement of two adolescent girls ever further into the forest in a post-apocalyptic account of the near future. Set in Redwood, California, it depicts a world where trees are gigantic and long-lasting while humans are diminutive and diminishing, while contemporary human technological society has fallen apart. Plants, trees, and the forest, and an increasingly intimate and Indigenous knowledge and relationship with these, play a key and ever-growing role in the novel and illuminate its otherwise dark vision of the future. Ultimately, the sisters’ taking of an increasingly plant-based perspective offers an alternative trajectory and path toward survival, sustenance, and self-sufficiency for the two young women. Although not necessarily written for young adults exclusively, the novel, whose international impact is evidenced by the fact that translated into over a dozen languages, made into a film in Canada, and adapted as a graphic novel in French, focuses on young adult protagonists and tells a post-apocalyptic tale that is both dark and inspiring in its vision of self-sufficiency and reintegration with nature, forest, and plants. It thus shows itself to be a work of young adult literature in many respects, as well as in its implied ecofeminist critique of capitalist society and a more sustainable vision of the future represented by the young. This article examines various plant geographies in Into the Forest and the way in which the forest represents a space of refuge from mankind and society; provides healing and sustenance; serves as an alternative abode; and represents a birthplace of the future. It argues that an increasingly plant-based perspective figures centrally in the book’s narrative arc from beginning to end, from its title and setting to the trajectory of its unfolding plot, and in its conclusion and vision of the future.

Fabrication of the optical lens on single-crystal germanium surfaces using the laser-assisted diamond turning

Single-crystal germanium, as an excellent infrared optical material, has been widely applied in X-ray monochromators, night vision systems, and gamma radiation detectors. However, how to obtain high-quality optical lenses on their surfaces still faces challenges due to their hard and brittle properties. To this end, this paper proposes the in situ laser-assisted diamond turning (ILADT) process, which is the combination of a laser heating technique and a single-point diamond turning process. The in situ laser heating technique is employed to enhance the surface quality of the workpiece material, while the single-point diamond turning process is utilized to fabricate optical lenses. Experimental results showed that optical lenses with high surface quality were successfully machined. The profile error is 0.135 μm, indicating the high machining accuracy. The surface roughness Sa of the aspheric lens is 0.909 nm, indicating the high machining quality achieved by the proposed ILADT process. Therefore, this study provides an effective approach for producing high-quality optical lenses on single-crystal germanium surfaces, which holds great promise for future applications in the manufacturing of optical lenses with exceptional quality.

Effects of different types of intraocular lens implantation on patient's visual quality and function after phacoemulsification

Objective: To explore the effects of different types of intraocular lens (IOL) implantation on patient's visual quality and function after phacoemulsification. Methods: The clinical data of patients with monocular cataract who underwent phacoemulsification in the Department of Ophthalmology, People's Hospital Affiliated to Shandong First Medical University between December 2021 and May 2023 were retrospectively analyzed. According to the types of IOL, the patients were divided into monofocal group, bifocal group and depth of focus extension group. Three months later, uncorrected distance visual acuity (UCDVA), best corrected distance visual acuity (BCDVA), uncorrected intermediate visual acuity (UCIVA), best corrected intermediate visual acuity (BCIVA), uncorrected near visual acuity (UCNVA) and best corrected near visual acuity (BCNVA) were detected. Contrast sensitivity and total wavefront aberration were measured by visual function analyzer. Satisfaction with visual quality was evaluated by hospital-made satisfaction questionnaire. Results: A total of 92 patients were included, with 31 males and 61 females, and their age was (61.8±5.2) years. There were 43, 28 and 21 cases in monofocal group, bifocal group and depth of focus extension group, respectively. No statistically significant difference was found in clinical baseline data among the three groups. UCIVA, UCDVA, BCIVA and BCDVA in depth of focus extension group were 1.01±0.13, 0.92±0.18, 1.21±0.19 and 1.20±0.23, respectively, which were higher than those in monofocal group (0.62±0.12, 0.74±0.13, 1.02±0.17, 1.07±0.19, respectively) and bifocal group (0.67±0.15, 0.78±0.14, 1.01±0.16, 1.01±0.18, respectively), while absolute value of spherical equivalent [(-0.42±0.07) D] was lower than that in the other two groups [ (-0.49±0.05) D and (-0.45±0.08) D] (both P<0.05). UCNVA and BCNVA in bifocal group were 0.91±0.18 and 1.25±0.18, which were higher than those in depth of focus extension group (0.63±0.24 and 1.19±0.17) (both P<0.05). There were no significant differences in contrast sensitivity among the three groups under day vision or between monofocal group and bifocal group under night vision (all P>0.05), but the contrast sensitivity was higher in depth of focus extension group under night vision (3.0, 6.0, 12.0 c/d) than other two groups (all P<0.05). The score of ocular discomfort was the highest in bifocal group, followed by depth of focus extension group and monofocal group (both P<0.05). The score of visual interference in bifocal group was lower than that in monofocal group and depth of focus extension group (both P<0.05). The scores of subjective feeling in bifocal group and depth of focus extension group were higher than that in monofocal group (both P<0.05). The reading score was the highest in bifocal group, followed by depth of focus extension group and monofocal group (both P<0.05). There was no significant difference in total low-order aberration among the three groups (P=0.472). The total aberration and higher-order aberration [(0.74±0.35) μm and (0.41±0.12) μm] were the highest in monofocal group, followed by bifocal group [(0.61±0.21) μm and (0.22±0.09) μm] and depth of focus extension group [(0.46±0.13) μm and (0.06±0.09) μm] (all P<0.05). Conclusions: IOL implantation with depth of focus extension can enhance visual range, night vision and contrast sensitivity, and thus effectively improve postoperative visual quality and function in cataract patients. The bifocal IOL can better improve the patient's UCNVA and BCNVA, resulting in high satisfaction with visual quality.

Proton and muon beam tests for ultra-fast MCP-PMT detectors

In collaboration with the North Night Vision Science and Technology (Nanjing) Research Institute Co. Ltd, researchers at the Institute of High Energy of Physics in China have successfully developed the 20-inch micro-channel-plate photomultiplier tube (MCP-PMT) that exhibits high detection efficiency (DE) for use in the Jiangmen Underground Neutrino Observatory (JUNO). Due to the long drift path of electrons from photocathode to MCP, the 20-inch MCP-PMT has a time resolution on the order of nanoseconds. Recently, the team has made advancements in ultra-fast MCP-PMTs (FPMTs), achieving picosecond-level time resolution with both 1-inch and 2-inch types. By now, prototypes featuring single-anode, 2 × 2 anodes, 4 × 4 anodes, and 8 × 8 anodes have been successfully manufactured and tested. The 8 × 8 anode FPMT, in particular, demonstrates a transit time spread (TTS) of 36 ps (Sigma) in single photon mode, thanks to its meticulously engineered structure. To assess the FPMT’s time performance under beam conditions, two beam tests were conducted at Fermi Lab and CERN. In these tests, the 8 × 8 pixel arrays of four distinct radiators, including LYSO, BGO, Pb glass and quartz glass, were paired with the 8 × 8 anodes FPMT. This setup involved the use of two radiator-coupled FPMT detectors for particle detection. The best coincidence time resolution recorded was 64 ps (Sigma) with a 120 GeV proton beam and 56 ps (Sigma) with a 108 GeV muon beam.

Real-time identification and visualization of Egyptian blue using modified night vision goggles

The possibility to use light in the visible spectrum to induce near-infrared luminescence in some materials, particularly Egyptian blue and related pigments, offers a significant advantage in terms of their detection. Since 2008, this property has been exploited to reveal the presence of those pigments even in tiny amounts on ancient and decayed surfaces, using a technical-photography method. This paper presents a new type of imaging device that enables real-time, easy, and inexpensive identification and mapping of Egyptian blue and related materials. The potential of the new tool is demonstrated by its effectiveness in detecting Egyptian blue within some prestigious sites: (a) Egyptian findings at Museo Egizio, Turin; (b) underground Roman frescoes at Domus Aurea, Rome; and (c) Renaissance frescoes by Raphael, Triumph of Galatea and Loggia of Cupid and Psyche, at Villa Farnesina, Rome. The device is based on night vision technology and allows an unprecedented fast, versatile, and user-friendly approach. It is employable by professionals including archeologists, conservators, and conservation scientists, as well as by untrained individuals such as students or tourists at museums and sites. The overall aim is not to replace existing photographic techniques but to develop a tool that enables rapid preliminary recognition, useful for planning the work to be carried out with conventional methods. The ability to immediately track Egyptian blue and related pigments, through real-time vision, photos, and videos, also provides a new kind of immersive experience (Blue Vision) and can foster the modern use of these materials in innovative applications and future technologies.

Near‐unity quantum efficiency wavelength‐tunable NIR phosphors (Sr2−yCay)Sc1−xSbO6: xFe3+ with excellent thermal stability

AbstractFe3+ ions as near‐infrared (NIR) activators are emerging as an alternative to Cr3+.1–5 However, it is a challenge to develop Fe3+‐activated NIR phosphors featuring tunable optical properties, high efficiency, and thermal stability. Herein, we present a series of near‐unity internal quantum efficiency (IQE), wavelength‐tunable and thermal stability NIR‐emitting phosphors Sr2−yCaySc1−xSbO6:xFe3+ (S2−yCyS1−xS:xFe3+). Sr2ScSbO6:1%Fe3+ (SSS:1%Fe3+) phosphor shows broadband NIR emission at 904 nm and near‐unity IQE under excitation at 300 nm. Experimental and theoretical calculation results demonstrate that introduced Ca ions could increase the bandgap value and Debye temperature (ΘD) of host from Eg = 3.702 eV, ΘD = 609 K of y = 0 to Eg = 3.801 eV, ΘD = 692 K of y = 2. Significantly, the resultant S2−yCyS1−xS:1%Fe3+ NIR phosphors show wavelength‐tunable emission from 904 to 952 nm and high IQE of 84.6%–97.5% as well as enhanced thermal stability (I423K/I298K = 76.9%) of Ca2ScSbO6:1%Fe3+ (CSS:1%Fe3+) in comparison with that (I423K/I298K = 70.6%) of pristine sample. We fabricated an NIR light‐emitting diodes (LED) device by using CSS:1%Fe3+ NIR phosphors with ultraviolet LED chip and demonstrated its potential applications in anticounterfeiting, information encryption, and night vision.

Application of depth feature recognition technology in foreign object recognition in distribution network monitoring video

Foreign objects identification in the distribution network is an important link in the security of electric power, and is of great significance to the normal transportation of electric power. At present, a lot of equipment in the distribution network is in the open air environment, facing a large number of foreign interference. These foreign objects not only bring potential safety hazards to the distribution network, but also easily lead to short circuit, causing power supply difficulties within the region. Therefore, the research first constructs an optimized triplet feature learning model. On this basis, the HOG-SVM depth feature recognition model is proposed. In HOG-SVM, AM is introduced to improve recognition accuracy. In addition, the research enhances the night vision ability of the model by standardizing the features in the image region block. The results show that the AP of the model is stable at more than 90.54%, the average FPR is 2.21%, and the average FNR is 3.17%. The performance of HOG-SVM is significantly better than that of traditional SVM. It verifies the contribution of this research in the field of foreign object recognition and application value in ensuring the security of distribution network.

Development of Multi Modal Image Fusion Techniques in Night Vision Technology Using Deep Learning

This study is aimed at exploring new development in nighttime image processing based on nighttime photography/night vision. We use various learning methodologies based on neural networks to develop multisensor data processing techniques. The ability of Convolutional Neural Networks (CNN) to enhance image quality and clarity under conditions of low light or at night is the focus of our research. To do this A large database has been created, containing 3200 images both taken from the internet as well as our own. This data is preprocessed, normalized and features expanded using some common methods of data augmentation in order to optimize model performance. We compared our proposed CNN model with existing literature through a series of experiments. Performance was measured using Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Feature Similarity Index (FSIM). The Results are now in. They showed that our model can improve various metrics with higher scores. And they show the real-time monitoring capabilities in urban streets for our model. This research brings multisensor image fusion based on night-adjacent techniques forward from night vision technology and provides insight into practical and potential future directions for using deep learning techniques to improve safety and security in many different environments.

Copper-cobalt cake as a potential source of germanium

Germanium is an important element used in crucial industry sectors like optical fibers for telecommunication or IR optics for night vision systems. However, its global output is limited. It is estimated that its annual global production is ca. 140 tons. Therefore, many world economies, including USA and EU, consider it as a critical raw material. One of the potential sources of germanium is zinc metallurgy. It is assumed that only 3% of germanium present in processed zinc ores is recovered. It was found that during the technological processes of Polish zinc smelters some by-products containing elevated germanium concentrations are produced. In the paper, potential germanium sources, including copper-cobalt cake obtained during the purification of zinc electrolyte and dross from the feeding furnace, are presented. The main components of the cake are cadmium, zinc, copper, nickel, cobalt, and lead, while the dross contains mainly zinc (>65%). Results of leaching tests for both materials using aqueous sulfuric acid solutions are shown. In the case of the cake, wet and dried material was investigated. It was found that the germanium leaching yield for the dried material reached 99%, while for the wet one was 46-86%, depending on leaching conditions (without or with oxidant). On the other hand, the germanium leaching yield for the dross reached 55%. Further processing of the solutions obtained after germanium leaching from the copper-cobalt cake was also analyzed. Two ways were proposed, including precipitation with tannic acid and solvent extraction with addition of complexing agents using a trioctylamine extractant.

Obtaining versatile Cr3+-activated phosphors with improved far-red emissions via host composition modulation

Cr3+-activated spinel-type phosphors have great potential in different application scenes due to their unique sharp and far-red (FR) emission. However, the multi-functionalization of these phosphors is still limited by their unsatisfied comprehensive properties. Herein, a simple composition engineering was used to explore versatile phosphors, using Ga3+ to substitute Al3+ to improve the optical performances of spinel LiAl5–xGaxO8:Cr3+. The substitution of Ga3+ evidently affects the crystal field environment of Cr3+ and further accounts for the luminescence optimization. Using the optimized phosphor, two sensitive thermometers based on fluorescence intensity ratio (FIR) technique were explored on account of the different temperature dependencies of 4T2→4A2 and 2E→4A2 emission and of R2 and R1 emission. The maximum relative sensitivity Sr are 1.29%/K at 323 K and 1.94%/K at 298 K, respectively, which are superior to that of the Ga3+-unsubstituted one. Besides, the Ga3+→Al3+ substitutions endow the resultant phosphors with larger atomic number (Zeff) and theoretical density, which is more conducive to improving X-ray-stimulated emission for X-ray detection. Finally, the potential applications of the developed phosphor are also reflected in plant growth and night vision surveillance, as it is shown to be capable of matching with the absorption of phytochrome PFR and visualizing objects in the dark. This contribution not only proves that the developed LiAl5–xGaxO8:Cr3+ FR phosphors are promising versatile platforms, but also provides an essential guidance for designing more novel multi-functional materials.

Simplifying vein detection for intravenous procedures: A comparative assessment through near‐infrared imaging system

AbstractThe intravenous (IV) injection procedure can be a challenging task, especially for individuals with thin veins, obesity, or patients with damaged and pigmented skin. Therefore, the IV procedure necessitates a portable medical device that can be used for academic demonstrations to train medical students or by health care professionals to perform venipuncture. Vein visualization with a vein detector is principally based on the interaction of blood components with wavelengths of the electromagnetic spectrum (EMS). In this paper, we first present the process of image formation in the spectral band of the near‐infrared region (NIR) of EMS. Then, we introduce the image acquisition system with image processing to extract the veins as a noninvasive vein detection method. A Raspberry Pi (Model 4B), along with a night vision camera, serves as an image acquisition tool to capture skin area illuminated by NIR. Following this, the data is transferred to the laptop where it can be filtered and processed using Python image processing tools before being viewed on the monitor. The results achieved through the device are quite encouraging, as the image recognition between veins and adjacent tissues from the skin sample can be clearly marked. The functionality, accuracy, and simplicity associated with this vein detection system make it a potential device for IV placement and the morphological study of disease detection.

Luminescence properties and energy transfer of broadband NIR phosphor Li2MgZrO4: 1.0%Cr3+, y%Yb3+

The discovery of high thermal stability, broad-band near-infrared (NIR) fluorescent phosphors holds significant potential in applications such as non-destructive testing, promoting plant growth, and night vision devices. In this study, a novel broad-band NIR phosphors Li2MgZrO4 (LMZ): 1.0 %Cr3+, y%Yb3+ were synthesized via a high-temperature solid-state reaction method, with the optimal doping concentration found to be y = 1.5. These phosphors exhibited broad NIR emission in the range of 700–1050 nm by effective energy transfer from Cr3+ to Yb3+. The maximum full width at half maximum (FWHM) of the Cr3+/Yb3+ co-doped LMZ phosphor is 270 nm. The thermal stability of the phosphors was improved with Yb3+ co-doping. Additionally, energy transfer from Cr3+ to Yb3+ was confirmed through luminescence spectra and lifetime analysis. Finally, NIR pc-LED devices composed of a 460 nm ultraviolet chip and LMZ: 1.0 %Cr3+, 1.5 %Yb3+ phosphors were fabricated, offering a highly promising source of invisible light. These results demonstrate the wide-ranging potential applications of this novel, high thermal stability, and ultra-broad NIR emitting fluorescent phosphor.