Search Results (208)

The palm-vein recognition system has garnered attention as a biometric technology due to its resilience to external environmental factors, protection of personal privacy, and low risk of external exposure. However, with recent advancements in deep learning-based generative models for image synthesis, the quality and sophistication of fake images have improved, leading to an increased security threat from counterfeit images. In particular, palm-vein images acquired through near-infrared illumination exhibit low resolution and blurred characteristics, making it even more challenging to detect fake images. Furthermore, spoof detection specifically targeting palm-vein images has not been studied in detail. To address these challenges, this study proposes the Fourier-gated feature-fusion network (FGFNet) as a novel spoof detector for palm-vein recognition systems. The proposed network integrates masked fast Fourier transform, a map-based gated feature fusion block, and a fast Fourier convolution (FFC) attention block with global contrastive loss to effectively detect distortion patterns caused by generative models. These components enable the efficient extraction of critical information required to determine the authenticity of palm-vein images. In addition, fractal dimension estimation (FDE) was employed for two purposes in this study. In the spoof attack procedure, FDE was used to evaluate how closely the generated fake images approximate the structural complexity of real palm-vein images, confirming that the generative model produced highly realistic spoof samples. In the spoof detection procedure, the FDE results further demonstrated that the proposed FGFNet effectively distinguishes between real and fake images, validating its capability to capture subtle structural differences induced by generative manipulation. To evaluate the spoof detection performance of FGFNet, experiments were conducted using real palm-vein images from two publicly available palm-vein datasets—VERA Spoofing PalmVein (VERA dataset) and PLUSVein-contactless (PLUS dataset)—as well as fake palm-vein images generated based on these datasets using a cycle-consistent generative adversarial network. The results showed that, based on the average classification error rate, FGFNet achieved 0.3% and 0.3% on the VERA and PLUS datasets, respectively, demonstrating superior performance compared to existing state-of-the-art spoof detection methods. Full article

This study investigates near-infrared (NIR)-induced, Phyto-enhanced, second harmonic generation-mediated photodynamic therapy (Phyto-SHG-PDT) using barium titanate (BT)/rhein/polyethylene glycol 100 (PEG100) and BT/Yemenite “Etrog” leaf extract/PEG100 nanoconjugates. We compare continuous-wave (CW), multi-line Argon-ion laser illumination in the NIR range with high-peak-power femtosecond (fs) 800 nm pulses. Under CW NIR light, BT/rhein nanoconjugates reduced PC3 prostate cancer cell viability by 18% versus non-irradiated controls (p < 0.05), while BT/extract nanoconjugates exhibited 15% dark toxicity. The observed SHG signal matched theoretical predictions and previous CW laser studies. Reactive Oxygen Species (ROS) scavenger 1,3-diphenyl-isobenzofuran (DPBF) showed reduced absorbance at 410 nm upon NIR illumination, indirectly supporting SHG emission at 400 nm from nanoconjugates. Under fs-pulsed laser exposure, pronounced two-photon absorption (TPA) and SHG effects were observed in both nanoconjugate types. Our results demonstrate the effectiveness of BT/rhein nanoconjugates under both laser conditions, while the BT/extract nanoconjugates benefited from high-power pulsed excitation. These results highlight the potential of BT-based Phyto-SHG-PDT nanoconjugates for NIR and blue light applications, leveraging nonlinear optical effects for advanced photochemical cancer therapies. Full article

Plastic waste and pollution is growing rapidly worldwide and most plastics end up in landfill or are incinerated because high-quality recycling is not possible. Plastic-type identification with a low-cost, handheld spectral approach could help in parts of the world where high-end spectral imaging systems on conveyor belts cannot be implemented. Here, we investigate how two fundamentally different handheld infrared spectral devices can identify plastic types by benchmarking the same analysis against a high-resolution bench-top spectral approach. We used the handheld Plastic Scanner, which measures a discrete infrared spectrum using LED illumination at different wavelengths, and the SpectraPod, which has an integrated photonics chip which has varying responsivity in different channels in the near-infrared. We employ machine learning using SVM, XGBoost, Random Forest and Gaussian Naïve Bayes models on a full dataset of plastic samples of PET, HDPE, PVC, LDPE, PP and PS, with samples of varying shape, color and opacity, as measured with three different experimental approaches. The high-resolution spectral approach can obtain an accuracy (mean ± standard deviation) of (0.97 ± 0.01), whereas we obtain (0.93 ± 0.01) for the SpectraPod and (0.70 ± 0.03) for the Plastic Scanner. Differences of reflectance at subsequent wavelengths prove to be the most important features in the plastic-type classification model when using high-resolution spectroscopy, which is not possible with the other two devices. Lower accuracy for the handheld devices is caused by their limitations, as the spectral range of both devices is limited—up to 1600 nm for the SpectraPod, while the Plastic Scanner has limited sensitivity to reflectance at wavelengths of 1100 and 1350 nm, where certain plastic types show characteristic absorbance bands. We suggest that combining selective sensitivity channels (as in the SpectraPod) and illuminating the sample with varying LEDs (as with the Plastic Scanner) could increase the accuracy in plastic-type identification with a handheld device. Full article

Functional near-infrared spectroscopy (fNIRS) is a non-invasive method for monitoring brain activity by detecting hemodynamic changes. Studies have shown that it can identify ictal and pre-ictal hemodynamic variations, supporting its potential use as a complement to electroencephalography (EEG) in epilepsy monitoring. This study explores an expanded illumination and detection approach utilizing wide-based optodes and increased emitter–detector separation (EDS) to enhance fNIRS sensitivity to cortical hemodynamic changes while minimizing scalp contamination. A Monte Carlo simulation was designed to assess signal amplitude and sensitivity of fNIRS with varying emitter and detector diameters (1–15 mm) and EDS (30–50 mm). Signal strength, grey matter to scalp path ratio (GSPR), and percentage signal change per absorption coefficients (AC) variation were analyzed. Sensitivity to changes in AC of superficial and deep grey matter (SGM, DGM) and scalp was assessed. Increasing emitter and detector diameters substantially increased total detected photon packet weights, enabling practical use at larger EDS. Sensitivity to SGM AC changes tripled at 50 mm EDS, while GSPR increased by 80%, indicating reduced signal contamination from the scalp. Sensitivity to deep cortical hemodynamic changes also improved. Therefore, wide-based fNIRS optodes with increased EDS can enhance seizure-related hemodynamic detection, potentially improving epilepsy diagnostics. Full article

System architecture was developed to solve the issues of short pupil distance and mismatch between the simulated wavelength range and the sensor in the simulator of small targets in space. The system consists of Liquid Crystal on Silicon (LCOS), a Polarizing Beam Splitter (PBS), a dual free-form surface-illumination system, and a long-exit-pupil-distance projection system. The innovatively designed long exit pupil distance projection system can achieve an exit pupil distance of 1250 mm, covering the visible and near-infrared bands from 400 to 950 nm. The dual free-form surface-illumination system reaches a divergence angle of ±4.3° and an illumination non-uniformity of 4.7%. Experimental validation shows that the system’s star position error is better than −3.94″, and the angular distance error between stars does not exceed −7.69″. The radiation simulation accuracy for stars ranging from magnitude 3 to 6 is between −0.049 and 0.085 magnitudes, demonstrating high-precision simulation capabilities for both geometric and radiation characteristics. The research results set a critical theoretical foundation for the development of high-fidelity space target simulators, and the proposed dual free-form surface-design method and wide-spectrum aberration compensation technology provide a new paradigm for precision optical system design. Full article

This study evaluates the optical and thermal performance of near-infrared (NIR)-blocking spectacle lenses at luminous transmittance grades of 0, 2, and 3. Ten lens types were tested, including clear, tinted, and NIR-blocking spectacle lenses (NIBSL). The NIR blocking rate was measured across 780–1100 nm and 1100–1400 nm wavelength bands. Color reproduction was assessed using sharpness (MTF 50), point spread function (PSF), and color accuracy (ΔE₀₀) under 1000 lux outdoor illumination. Thermal insulation was analyzed by monitoring porcine skin temperature at 36 °C and 60 °C under each lens type. As a result, the NIBSL showed better near-infrared blocking performance than other types of lenses in both wavelength ranges, and the coated NIBSL blocked near-infrared more effectively than the polymerized lenses. Compared with other types of lenses, NIBSL showed no difference in object identification, color recognition, and reproducibility, so there is no problem in using them together. Strong correlations were observed between lens surface temperature and underlying pig skin temperature, and inverse correlations between NIR blocking rate and pig skin temperature gradient. These findings confirm that NIBSL offer enhanced protection against NIR-induced thermal effects without compromising optical performance, supporting their use in daily environments for ocular and skin safety. Full article

Accurately estimating 3D human pose and body shape from a single monocular image remains challenging, especially under poor lighting or occlusions. Traditional RGB-based methods struggle in such conditions, whereas single-pixel imaging (SPI) in the Near-Infrared (NIR) spectrum offers a robust alternative. NIR penetrates clothing and adapts to illumination changes, enhancing body shape and pose estimation. This work explores an SPI camera (850–1550 nm) with Time-of-Flight (TOF) technology for human detection in low-light conditions. SPI-derived point clouds are processed using a Vision Transformer (ViT) to align poses with a predefined SMPL-X model. A self-supervised PointNet++ network estimates global rotation, translation, body shape, and pose, enabling precise 3D human mesh reconstruction. Laboratory experiments simulating night-time conditions validate NIR-SPI’s potential for real-world applications, including human detection in rescue missions. Full article

Marine steel structures face severe corrosion risks due to harsh environmental conditions, posing significant logistical, economic, and safety challenges for inspection and maintenance. Traditional corrosion assessment methods are costly, labor-intensive, and potentially hazardous. This study evaluated the capabilities of visible-to-near-infrared hyperspectral imaging (HSI) for automating corrosion detection and severity classification in steel samples subjected to accelerated corrosion conditions simulating marine exposure. Marine steel coupons were partially coated to simulate protective paint and immersed in natural brackish water from the Panama Canal, creating varying corrosion levels. Hyperspectral images were acquired in controlled illumination conditions, calibrated radiometrically, and reduced in dimensionality via principal component analysis (PCA). Four machine learning models, including k-nearest neighbors, support vector machine, random forest, and multilayer perceptron, were tested for classifying corrosion severity. The multilayer perceptron achieved the highest accuracy at 96.18%, clearly distinguishing among five defined corrosion stages. These findings demonstrate that hyperspectral imaging, coupled with machine learning techniques, provides a viable, accurate, non-destructive methodology for assessing marine steel corrosion, potentially reducing costs, improving safety, and streamlining maintenance procedures. Full article

Burgeoning two-dimensional (2D) materials provide more opportunities to overcome the shortcomings of silicon-based photodetectors. However, the inevitable carrier loss in the 2D material/Si heterojunction has seriously hindered further improvement in responsivity and detection speed. Here, we propose a graphene/PtSe₂/ultra-thin SiO₂/Si photodetector (PD) with multiple optimization mechanisms. Due to the fact that photo-generated carriers can travel in the graphene plane toward the Au electrode, the introduction of a top graphene contact with low sheet resistance provides a carrier collection path in the vertical direction and further restricts the carrier recombination behavior at the lateral grain boundary of PtSe₂ film. The ultra-thin SiO₂ passivation layer reduces the defects at the PtSe₂/Si heterojunction interface. As compared to the counterpart device without the graphene top contact, the responsivity, specific detectivity, and response speed of graphene/PtSe₂/ultra-thin SiO₂/Si PD under 808 nm illumination are improved to 0.572 A/W, 1.50 × 10¹¹ Jones, and 17.3/38.8 µs, respectively. The device can detect broad-spectrum optical signals as measured from 375 nm to 1550 nm under zero bias. The PD line array with 16-pixel units shows good near-infrared imaging ability at room temperature. Our study will provide guiding significance for how to improve the comprehensive properties of PDs based on 2D/Si heterostructure for practical applications. Full article

Solar steam generation (SSG) has garnered significant attention for its potential in water purification applications. While composites with physically combined structures based on semiconductors or biomass have been developed for SSG, there remains a critical need for low-cost, high-efficiency devices. In this study, TiO₂ composites exhibiting excellent stability, high solar absorption, porous microstructure, and hydrophilic surfaces were identified as effective materials for SSG and water purification for the first time. A novel SSG device was designed by decorating TiO₂ onto three-dimensional carbonized Osmanthus fragrans leaves (TiO₂/carbonized OFL). Compared to directly carbonized OFL (without TiO₂) and Osmanthus fragrans leaves with templated TiO₂ (OFL-templated TiO₂), the TiO₂/carbonized OFL carbon composites demonstrated enhanced solar absorption, achieving over 99% in the visible region and more than 80% in the near-infrared region. Under solar illumination of 1 kW·m⁻², the TiO₂/carbonized OFL device achieved a high water evaporation rate of 2.31 kg·m⁻²·h⁻¹, which is 1.6 times higher than that of carbonized OFL and 3.45 times higher than OFL-templated TiO₂. Additionally, the TiO₂/carbonized OFL system exhibited remarkable efficiency in treating pharmaceutical wastewater, with a chemical oxygen demand (COD) removal efficiency of 98.9% and an ammonia nitrogen removal efficiency of 90.8% under solar radiation. Full article

Accurate detection of textile composition is a major challenge for textile reuse/recycling. This paper investigates the feasibility of identification of textile materials using a Near Infra-Red (NIR) camera. A transportable metric has been defined which could be capable of identification and distinction between cotton and polyester. The NIR camera provides a single data value in the form of the “intensity” of the exposed light at each pixel across its 2D pixel array. The feasibility of textile material identification was investigated using a combination of various statistical methods to evaluate the output images from the NIR camera when a bandpass filter was attached to the camera’s lens. A repeatable and stable metric was identified and was shown to be independent of both the camera’s exposure setting and the physical illumination spread over the textiles. The average value of the identified metric for the most suitable bandpass filter was found to be 0.68 for cotton, with a maximum deviation of 2%, and 1.0 for polyester, with a maximum deviation of 1%. It was further shown that carbon black dye, a known challenge in the industry, was easily detectable by the system, and, using the proposed technique in this paper, areas that are not covered by carbon black dye can be identified and analysed. Full article

Railway travel is an eco-friendly means of transportation, and passengers are spending increasing amounts of time on trains while engaging in various activities. As a major factor affecting railway passengers’ comfort, we investigated the effects of lighting. Korean train cars are required to have two rows of light-emitting diode lights with a minimum illuminance of 500 lx, so we examined changes in cerebral blood flow under various illuminance conditions around this threshold value. We used functional near-infrared spectroscopy to measure prefrontal cortex activation in 29 college students under illuminance values of 300, 500, and 800 lx and color-temperature values of 2700 K (bulb color), 4000 K (white color), and 5500 K (blue color). Mean brain activity values were compared using analysis of variance. Of the 48 channels, significant interaction effects between color and illuminance on brain activation responses were observed for channel 38, as well as in the right dorsolateral prefrontal cortex among the different brain regions of the Brodmann area (p < 0.05). Oxygenated hemoglobin concentrations had consistently negative values for all the treatment combinations, and individual treatment analyses based on single-sample Student’s t-tests showed different degrees of brain activation among channels and Brodmann areas. Meanwhile, a comparison of absolute values indicated that an illuminance level of 500 lx was more comfortable than levels of 300 and 800 lx, and that white color was more comfortable than bulb color and blue color. These results provide a scientific basis for the design of train cars that improve passenger comfort and satisfaction, which is anticipated to enhance the quality of railway services. Full article

Photodynamic and photothermal therapies with IR780 have gained exponential interest, and their photophysical properties have demonstrated promise for use in antitumor and antimicrobial chemotherapy. IR780 and its derivatives are valuable in labeling nanostructures with different chemical compositions for in vitro and in vivo fluorescence monitoring studies in the near-infrared (NIR) spectrum. The current literature is abundant on this topic, particularly with applications in the treatment of different types of cancer using laser illumination to produce photodynamic (PDT), photothermal (PTT), and, more recently, sonodynamic therapy (SDT) approaches for cell death. This review aims to update the state of the art concerning IR780 photosensitizer as a theranostic agent for PDT, PTT, SDT, and photoacoustic (PA) effects, and fluorescence imaging monitoring associated with different types of nanocarriers. The literature update concerns a period from 2017 to 2024, considering, more specifically, the in vivo effects found in preclinical experiments. Some aspects of the labeling stability of nanostructured systems will be discussed based on the evidence of IR780 leakage from the nanocarrier and its consequences for the reliable analysis of biological data. Full article

Genetically encoded voltage indicators (GEVIs) allow for the cell-type-specific real-time imaging of neuronal membrane potential dynamics, which is essential to understanding neuronal information processing at both cellular and circuit levels. Among GEVIs, near-infrared-shifted GEVIs offer faster kinetics, better tissue penetration, and compatibility with optogenetic tools, enabling all-optical electrophysiology in complex biological contexts. In our previous work, we employed the directed molecular evolution of microbial rhodopsin Archaerhodopsin-3 (Arch-3) in mammalian cells to develop a voltage sensor called Archon1. Archon1 demonstrated excellent membrane localization, signal-to-noise ratio (SNR), sensitivity, kinetics, and photostability, and full compatibility with optogenetic tools. However, Archon1 suffers from low brightness and requires high illumination intensities, which leads to tissue heating and phototoxicity during prolonged imaging. In this study, we aim to improve the brightness of this voltage sensor. We performed random mutation on a bright Archon derivative and identified a novel variant, monArch, which exhibits satisfactory voltage sensitivity (4~5% ΔF/F_AP) and a 9-fold increase in basal brightness compared with Archon1. However, it is hindered by suboptimal membrane localization and compromised voltage sensitivity. These challenges underscore the need for continued optimization to achieve an optimal balance of brightness, stability, and functionality in rhodopsin-based voltage sensors. Full article

Vegetation indices, especially the normalized difference vegetation index (NDVI), are widely used in urban vegetation assessments. However, estimating the vegetation abundance in urban scenes using the NDVI has constraints due to the complex spectral signature related to the urban structure, materials and other factors compared to natural ground surfaces. This paper employs the 3D discrete anisotropic radiative transfer (DART) model to simulate the spectro-directional reflectance of synthetic urban scenes with various urban geometries and building materials using a flux-tracking method under shaded and sunlit conditions. The NDVI is calculated using the spectral radiance in the red (0.6545 μm) and near-infrared bands (0.865 μm). The effects of the urban material heterogeneity and 3D structure on the NDVI, and the performance of three NDVI-based fractional vegetation cover (FVC) inversion algorithms, are evaluated. The results show that the effects of the building material heterogeneity on the NDVI are negligible under sunlit conditions but not negligible under shaded conditions. The NDVI value of building components within synthetic scenes is approximately zero. The shaded road exhibits a higher NDVI value in comparison to the illuminated road because of scattering from adjacent pixels. In order to correct the effects of scattering caused by building geometry, the reflectance of the Landsat 8/OLI image is corrected using the sky view factor (SVF) and then used to calculate the FVC. Jilin-1 satellite images with high spatial resolution (0.5 m) are used to extract the vegetation cover and then aggregated to 30 m spatial resolution to calculate the FVC for validation. The results show that the RMSE is up to 0.050 after correction, while the RMSE is 0.169 before correction. This study makes a contribution to the understanding of the effects of the urban 3D structure and material reflectance on the NDVI and provides insights into the retrieval of the FVC in different urban scenes. Full article