Influence Of Ambient Light Research Articles

A smart lab on a wearable microneedle patch with convolutional neural network‐enhanced colorimetry for early warning of syndrome of inappropriate antidiuretic hormone secretion

AbstractFrequent nocturia‐induced nighttime visits aggravate falls in seniors, requiring synthetic antidiuretic drugs that risk the dangerous syndrome of inappropriate antidiuretic hormone secretion (SIADH), thus the detection of sodium ion and uric acid alterations during treatment is obligatory for drug‐safe management. Herein, we design a convolutional neural network (CNN)‐enhanced smart wearable microneedle array‐based colorimetric (WMNC) sensor to independently detect in vivo interstitial fluid (ISF) sodium ions and uric acid alterations. The WMNC sensor is composed of a vacuum tube‐driven microneedle array patch and a built‐in colorimetric sensing paper, enabling an efficient ISF extraction and rapid colorimetric assay. Furthermore, leveraging self‐designed CNNs, the WMNC sensor efficiently eliminates the influence of ambient light on colorimetric outcomes, facilitating a rapid and accurate colorimetric result classification. This study provides an ISF‐based rapid, intuitionistic, user‐friendly, wearable point‐of‐care technique for the elderly suffering from nocturia in monitoring their health status for early warnings of SIADH.

P‐44: A Smart Eye Tracking System Based on Linear Array Sensors

Eye tracking as an important human‐machine interface plays avital role in immersive displays such as augmented reality (AR) and virtual reality (VR). Different from near infrared (NIR) camerabased methods, the proposed corneal reflection method based on principle of eyeball co‐vision takes advantage of using eye‐safe 940‐ nm vertical cavity surface emitting laser (VCSEL) and dual‐column linear array sensor (DCLAS) to obtain coordinates of the eyeball's moving positions through detecting its reflected light. The DCLAS not only delivers high sensitivity at eye‐safe NIR wavelength, but also has high spatial resolution for position accuracy and wide dynamic range to suppress ambient light influence. Together with low power consumption, good wearability, low data redundancy and simple computing algorism, a great promise can be made to enable smart eye tracking for AR/VR.

Global phase accuracy enhancement of structured light system calibration and 3D reconstruction by overcoming inevitable unsatisfactory intensity modulation

Mainstream fringe projection profilometry (FPP) faces challenges in measuring low signal-to-noise ratio intensity modulation areas, especially in shadow areas on objects and black areas on calibration plates, causing pseudo phases and obvious nonlinear calibration errors in 3D measurement. To address these issues concurrently, we proposed a cyclic phase-shifts difference (CPSD) module based on phase-shifting gratings. CPSD uses double-layer circulation difference to retain the pixels with higher light intensity eliminating the influence of ambient light and finally creates a mask removing and correcting black and shadow areas. Without further post-processing and projection operation, we achieved the global phase accuracy enhancement and obtained high-precision 3D point clouds without pseudo points. The method’s efficacy was proven through experiments on three kinds of calibration planes, achieving a significant reduction in mean absolute error (MAE) and standard deviation (STD) in plane reconstruction (up to 50.9% and 56.1% respectively). We believe that CPSD has enormous potential for wide application across various FPP-related fields. (Code and data are avaliable at: https://github.com/LiYiMingM/CPSD_shadow_and_black_area_phase_correction_in_SL3D)

Machine learning approach for ambient-light-corrected parameters and the Pupil Reactivity (PuRe) score in smartphone-based pupillometry.

The pupillary light reflex (PLR) is the constriction of the pupil in response to light. The PLR in response to a pulse of light follows a complex waveform that can be characterized by several parameters. It is a sensitive marker of acute neurological deterioration, but is also sensitive to the background illumination in the environment in which it is measured. To detect a pathological change in the PLR, it is therefore necessary to separate the contributions of neuro-ophthalmic factors from ambient illumination. Illumination varies over several orders of magnitude and is difficult to control due to diurnal, seasonal, and location variations. We assessed the sensitivity of seven PLR parameters to differences in ambient light, using a smartphone-based pupillometer (AI Pupillometer, Solvemed Inc.). Nine subjects underwent 345 measurements in ambient conditions ranging from complete darkness (<5 lx) to bright lighting (≲10,000 lx). Lighting most strongly affected the initial pupil size, constriction amplitude, and velocity. Nonlinear models were fitted to find the correction function that maximally stabilized PLR parameters across different ambient light levels. Next, we demonstrated that the lighting-corrected parameters still discriminated reactive from unreactive pupils. Ten patients underwent PLR testing in an ophthalmology outpatient clinic setting following the administration of tropicamide eye drops, which rendered the pupils unreactive. The parameters corrected for lighting were combined as predictors in a machine learning model to produce a scalar value, the Pupil Reactivity (PuRe) score, which quantifies Pupil Reactivity on a scale 0-5 (0, non-reactive pupil; 0-3, abnormal/"sluggish" response; 3-5, normal/brisk response). The score discriminated unreactive pupils with 100% accuracy and was stable under changes in ambient illumination across four orders of magnitude. This is the first time that a correction method has been proposed to effectively mitigate the confounding influence of ambient light on PLR measurements, which could improve the reliability of pupillometric parameters both in pre-hospital and inpatient care settings. In particular, the PuRe score offers a robust measure of Pupil Reactivity directly applicable to clinical practice. Importantly, the formulae behind the score are openly available for the benefit of the clinical research community.

In‐panel ambient light eliminating differential circuit applied to active pixel fingerprint sensor

AbstractIn this paper, we present a novel approach to counter the influence of ambient light on photodetectors used in applications like biometric recognition and environmental sensing. The proposed solution introduces a circuit‐based technique that utilizes signal differencing to subtract ambient light signals before they reach the integrated circuit (IC). The process involves row and column differential signals, akin to analog circuit differential amplifiers. Simulations validate the circuit's functionality, showing its effectiveness in reducing ambient light impact. However, image reconstruction after differencing introduces blurriness due to the accumulation of noise. An alternative bidirectional fusion method is suggested, resulting in a clearer representation of features without noise accumulation. This innovative approach promises to enhance photodetector performance in challenging lighting conditions for various applications.

The intensity inhibition strategy for indoor light sources during structured light measurement

During the measurement of structured light, different types of ambient light may cause some interference with the imaging process of grating projection. Therefore, this paper provides a descriptive method of the intensity of ambient light based on the polarization information. This method describes the degree of influence of ambient light on the grating projection system with the Mueller matrix of the target object and then processes the grating image in the frequency domain to reduce the influence of ambient light on the grating projection system. The final experimental results indicate the correctness of the proposed method.

Unveiling the influence of ambient lighting on stimulating ultraviolet luminescence of deep-trap phosphors

Glow-in-the-daylight is a fascinating luminescence phenomenon displayed by certain storage phosphors that emit ultraviolet light upon being stimulated by ambient lighting. In this study, we investigate the influence of indoor lighting on the glow-in-the-daylight emission of a co-doped garnet phosphor, Y3Al5O12:Pr3+,Eu3+, known for its deep trap that effectively retains energy. Our experimental results demonstrate an interesting observation that, following x-ray radiation at room temperature, this phosphor exhibits negligible persistent luminescence in darkness but emits intense ultraviolet light peaking at 318 nm under indoor lighting conditions. This emphasizes the crucial role played by ambient lighting in releasing stored energy. Our findings not only shed light on the influence of indoor illumination dose and spectral distribution on the persistently stimulated luminescence but also expand our exploration to various ultraviolet phosphors with deep traps, with the aim of uncovering novel materials applicable in glow-in-the-daylight scenarios.

Nationwide survey on the current situation of quality control of diagnostic displays in Japan

The Japan Association of Radiological Technologists (JART) and the Japan Medical Imaging and Radiological Systems Industries Association jointly conducted a nationwide survey to reveal the current situation of diagnostic displays in Japan using a questionnaire on the performance and quality control (QC) of diagnostic displays for mammography and common use. The questionnaire for radiological technologists (RTs) was distributed via email to 4519 medical facilities throughout Japan, where RTs affiliated with JART were employed; 613 (13.6%) facilities responded. Diagnostic displays with suitable maximal luminance (500cd/m2 or higher for mammography and 350cd/m2 or higher for common use) and resolution (5 megapixels for mammography) have been widely used. However, while 99% of the facilities recognized the necessity of QC, only approximately 60% implemented it. This situation arose due to several barriers to QC implementation, such as insufficient devices, time, staff, knowledge, and the recognition of QC as a duty. The implementation of QC can lead to the avoidance of incidents or accidents caused by a decrease in luminance, variation in luminance response, and the influence of ambient light. Moreover, the barriers discouraging the implementation of QC are mainly related to a lack of human resources and budgets. Therefore, to popularize the QC of diagnostic displays in all facilities, it is crucial to identify countermeasures to eliminate these barriers and to continue positive actions for popularization.

Influence of Ambient Light on the Radiation-Induced Attenuation of Germanosilicate Optical Fibers in the Visible and Near-Infrared Domains

We investigated the influence of the ambient light on the Radiation-Induced Attenuation (RIA) of Ge-doped optical fibers measured at the telecommunication wavelengths when exposed to a <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">60</sup> Co source, and in the visible and Near-InfraRed (NIR) domains when exposed to X-rays. From our results, it is possible to observe that this class of optical fibers are sensitive to the ambient light. Indeed, in all cases, their RIA value changes depending on the illumination conditions. In particular, the γ-ray irradiations revealed jumps in the measured RIA when changing the lamp of the irradiation chamber, whereas the X-ray irradiations reported that the relative photobleaching effect caused by the ambient light increases with the wavelength, up to ~1300 nm. The spectral study revealed no direct correlation between the absorption bands of the known Ge-related point defects and the external photobleaching phenomenon.

Physical-Layer Network Coding Enhanced Visible Light Communications Using RGB LEDs

Compared with traditional radio frequency (RF)-based techniques, the advantages of wider bandwidth, higher security, and stronger electromagnetic immunity (EMI) capability make visible light communications (VLC) a good candidate technology for the 6th generation (6G) wireless communications. Red, green, and blue (RGB) light-emitting diodes (LEDs) based VLC has become an important research branch due to its low price and high reliability. However, the saturation of photodiode (PD) caused by the ambient background light may seriously degrade the bit error rate (BER) performance of an RGB-VLC system's three spatially uncoupled information streams (i.e., red, green, and blue LEDs can transmit different data packets simultaneously) in practical applications. To mitigate the ambient light interference in point-to-point RGB-VLC systems, we propose, PNC-VLC, a network-coded scheme that uses two LEDs with the same color at the transmitter to transmit two different data streams and we make use of the naturally overlapped signals at the receiver to formulate physical-layer network coding (PNC). The adaptivity of PNC-VLC could effectively improve the BER degradation problem caused by the saturation of PD under the influence of ambient light. We conducted simulations based on the parameters of commercial off-the-shelf (COTS) products to prove the superiority of the PNC-VLC under the influence of four typical illuminants. Simulation results show that the PNC-VLC system can maintain a better and more stable system BER performance under different ambient background light conditions. Remarkably, with 2/3 throughput efficiency, PNC-VLC can bring 133.3% gain to the BER performance when compared with the traditional RGB-VLC systems under the Illuminant A interference model, making it a good option for VLC with unpredictable ambient background interferences.

Anaemia detection based on sclera and blood vessel colour estimation

Anaemia is a global public health problem with major consequences for human health. Noninvasive methods must be investigated to determine a sick person's anaemic status or conduct screening campaigns, especially in resource-constrained areas of the earth. This study aims to prove that the colour of the sclera and scleral blood vessels extracted from digital images of the eye can be used to check the anaemic status of a person. To date, we have not found in the literature other studies that have attempted this promising approach. We propose a novel pipeline for anaemia estimation consisting of three main contributions: a sclera segmentation algorithm applied to near-taken digital photos of the eye, a vessel extraction algorithm, and a classifier to predict the anaemic status of a person vs normal controls. This study was based on the public dataset Eyes-defy-anaemia, which contains 218 eye pictures taken with a special device that removes any ambient light influence. Very interesting results have been achieved for the sclera segmentation task with good precision (88.53), recall (82.53) and F1 (84.10). The colour features and haemoglobin value appear to be well related allowing us to obtain an F2 score in the anaemia detection task of 86.4% using colour features from the whole sclera and of 83.8% using only vessels’ colour features.

An Optical POCT Device for Colorimetric Detection of Urine Test Strips Based on Raspberry Pi Imaging

Urine examinations are widely applied in hospitals using urine test strip analyzers or other sophisticated professional instruments. However, such methods are inconvenient health monitoring of patients at home. Herein, we construct an optical device for point-of-care testing (POCT) for urine analysis at home or on the spot. A black box and color calibration curve are established to eliminate the influence of ambient light with an independent internal lighting system included in the device. A Raspberry Pi with a CSI camera is programmed to automatically collect the strip images and identify the HSV values of the image with an image processing algorithm. During this process, these corrected colors are converted to concentration values by preloaded standard curves. Under optimal conditions, the proposed POCT device can quantitatively and automatically detect glucose within 1 min, with linear detection ranging from 2 mM to 60 mM and a detection limit of 1.16 mM. In addition, the device demonstrates satisfactory accuracy and quantitative analysis of ketone bodies, glucose, protein, occult blood, pH, and leukocytes in human urine samples with high-resolution concentrations, achieving results similar to those obtained with hospital instruments. The proposed device is portable and user-friendly, providing convenient colorimetric analysis for urine. Furthermore, the proposed device also has considerable potential for the development of in vitro diagnosis methods through combination with other test strips.

High-accuracy and efficient method for calibrating spatial laser beam based on optimized PSD

The laser sensing technique with visual laser beam has been an increasing interest in large-scale 3D measurement. However, a major limitation has been the high-accuracy positioning of laser beam in 3D space. An efficient calibration method of spatial laser beam in large-scale measurement is proposed in this paper. A novel PSD-based laser detecting device is presented to accurately collect the laser beam data. The 3D coordinates of points on the laser beam can be transformed from the PSD coordinate system to the world coordinate system by the pre-calibrated reference points and spatial transformation analysis. Furthermore, the optimized method of PSD data processing is proposed to reduce the influence of ambient light on detecting laser point coordinates. Finally, the spatial posture of laser beam can be obtained by linear fitting from the high-accuracy acquired points. The calibration process is greatly simplified compared with the existing methods. The experimental results show that the average deviation between the obtained spatial points and the fitted line is less than 0.015 mm within 5 m. The proposed method is applied to non-orthogonal shafting theodolites, and the point measurement average error is less than 0.17 mm, and the distance measurement average error is less than 0.16 mm.

3D surface reconstruction scheme for dynamic objects: Principle and implementation

This paper introduces a high-speed, low-cost and easy-to-implement three dimensional (3D) surface measurement approach for dynamic objects. First, we proposed a new dual-frequency dual-step phase shift method to extract unwrapped phase, which has high accuracy and few fringes. We also analyzed the influence of ambient light on the proposed method. Secondly, we compare a variety of dither binarization methods and chose a suitable error diffusion kernel. Finally, we introduce the implementation of the dynamic 3D measurement system. Experiments on 3D measurement of dynamic objects demonstrate the valid of the proposed scheme. Further comparison of the phase accuracy between the proposed method and existing methods confirms the robustness of the proposed dual-frequency dual-step phase shift method.

P‐63: Design and Fabrication of Wide‐Viewing‐Angle Ambient Light Rejection Front Projection Screen

The image quality of projection displays is decreased by ambient light. This paper proposed a screen that composed of a microlens array film with printed black ink stripes on back side and a matte‐white‐reflection film to reduce the influence of ambient light in the front projection system. The ambient light was guided to light absorptive black ink by micro‐lens and thus enhance the contract ratio of the image in the bright environment. A proposed screen performed a better than 6.5 times improvement in image contrast ratio without sacrificing viewing angle compared to a matte‐white screen under ambient light condition was demonstrated. The proposed projection screen works well in short‐to‐standard throw projectors and good for home or public applications.

Tactile-Based Fabric Defect Detection Using Convolutional Neural Network With Attention Mechanism

This paper proposes a fabric structure defect detection method based on the vision-based tactile sensor. The result will be robust by using the tactile sensor regardless of dyeing patterns which can influence the result if some other sensors are used, e.g., vision perception. It also reduces the influence of ambient light on defect detection. Therefore, the proposed method can be more robust and universal than conventional visual methods. A robotic arm equipped with the tactile sensors was used to automate and standardize the data collection process and construct fabric datasets. In addition, a convolutional neural network integrated with attention mechanism in the channel domain was developed to detect fabric types. The proposed network employed frequency domain filtering to remove or weaken the influence of normal fabric texture information to improve defect detection efficiency and accuracy. Finally several experiments were conducted to demonstrate the proposed method’s superiority to a visual defect detection method for detecting structural defects. In addition, the efficiency of the proposed method is evaluated. Experimental results show that the proposed method is feasible and efficient to meet the real-world detection requirements.

Fractional coverage rather than green chromatic coordinate is a robust indicator to track grassland phenology using smartphone photography

Cost-effective and accurate methods are critical in monitoring grassland phenology. Smartphones have great potential for tracking phenological changes owing to their easy operation and flexible sampling, especially for experimental treatments on grassland phenology at local scale. However, it remains an open question for an accurate and robust measure in tracking plant phenology under various light conditions when using smartphones. To fill this gap, we compared green chromatic coordinate (GCC) and fractional coverage (FC) produced by three widely-used smartphone types across varying light conditions. We also explored the effects of experimental warming and N addition on grassland spring phenology using smartphone photography. We found that light conditions affected GCC values derived from various smartphones. The percentile method did not reduce the influence of various light conditions on GCC calculation. When using one type of smartphone, other techniques (e.g., shading strong sunlight) were required to minimize the effect of light on mean GCC during photography, but they did not work for FC. Based on this method, three smartphone types generated similar phenological metrics (i.e., start, peak and end of growing season) detected from GCC or FC. GCC and FC produced synchronous seasonal trajectories and similar phenological metrics throughout the growing season. We also found that experimental warming advanced spring phenology in the relatively wet year of 2018, but delayed it in the dry year of 2019. In contrast, N addition had little influence on spring phenology. Our results revealed that overlooking the influence of ambient light and smartphone types on GCC might lead to uncertainties in phenological measurement. Robust FC metrics extracted from smartphone photography detected grassland phenology differences in response to warming and N deposition. These findings provide evidence that FC is a robust indicator to accurately monitor grassland phenology using smartphone photography. Their utility resonates with those monitoring many experimental plots or sites with various light conditions.

On-Site Calibration Method for Line-Structured Light Sensor-Based Railway Wheel Size Measurement System.

Line-structured light has been widely used in the field of railway measurement, owing to its high capability of anti-interference, fast scanning speed and high accuracy. Traditional calibration methods of line-structured light sensors have the disadvantages of long calibration time and complicated calibration process, which is not suitable for railway field application. In this paper, a fast calibration method based on a self-developed calibration device was proposed. Compared with traditional methods, the calibration process is simplified and the calibration time is greatly shortened. This method does not need to extract light strips; thus, the influence of ambient light on the measurement is reduced. In addition, the calibration error resulting from the misalignment was corrected by epipolar constraint, and the calibration accuracy was improved. Calibration experiments in laboratory and field tests were conducted to verify the effectiveness of this method, and the results showed that the proposed method can achieve a better calibration accuracy compared to a traditional calibration method based on Zhang’s method.

A Novel Multicamera System for High-Speed Touchless Palm Recognition

Palm-related biometrics have been widely studied for a long time, as the palm contains many distinctive patterns. However, most of the existing systems are designed to work within an ideal environment, such as in front of a unicolor background or in a large enclosure. Those preconditions can avoid influences of ambient light and hand distance change, but at the same time, they also limit the applications of palm recognition. In the work reported in this paper, we designed a novel red-green-blue and depth-based four-camera system that can capture the palm-related images separately in real time. The techniques of region-of-interest (ROI) location, ROI alignment, and light-source intensity optimization were studied. The ROI location method is modified to increase the robustness of hand gesture variation. Based on the depth information, we proposed the coordinate mapping and inclination rectification methods to obtain aligned ROI pairs. Using this device, we collected a video-based multimodal palm image database. After the parameter optimization and information fusion, the equal-error-rate of our approach on this database is lower than 0.47%. The recognition rate obtained from the support-vector-machine-based fusion is higher than 99.8%. The experimental results prove that the proposed system achieves advantages of anti-spoofing, high speed, high accuracy, and small size.

Improved computer-generated moiré profilometry with flat image calibration.

An improved computer-generated moiré profilometry (CGMP) with flat image calibration is proposed. In CGMP, the purification of the AC component plays a decisive role. While a composite grating modulated with both the sinusoidal grating and its background light substitutes for the sinusoidal grating itself, the sinusoidal deformed pattern and flat image can be demodulated from the captured pattern. It is found that the sinusoidal deformed pattern and flat image may deviate, which is caused by ambient light. So flat image calibration is conducted to obtain a purer AC component that can effectively suppress the influence of ambient light and ensure the measurement accuracy, even if spectrum aliasing exists. Experimental results show the feasibility and validity of the proposed method.