White Point Research Articles

Photoluminescence color-tuning with polymer-dispersed fluorescent films containing two fluorinated diphenylacetylene-type fluorophores.

The development of organic light-emitting devices has driven demand for new luminescent materials, particularly after the 2001 discovery of aggregation-induced emission. This study focuses on fluorinated diphenylacetylene-based luminescent molecules, revealing that specific molecular modifications can enhance fluorescence and achieve a wide range of photoluminescence colors. A simple and effective luminescence color-tuning method is proposed to investigate the photoluminescence behavior of two-component polymer dispersion films blended with two types of fluorinated diphenylacetylenes, namely blue- and yellow- or red-fluorescent fluorinated diphenylacetylenes. It is confirmed that if blue and green-yellow or yellow fluorophores are blended in appropriate ratios, a binary blend with color coordinates (0.20, 0.32) can be achieved, which approaches the white point of pure white emission. These findings contribute to the development of effective lighting and display devices as new white-light-emitting materials.

Spectral characteristics and luminescence applications of Eu3+-activated fluorosilicate Na2MgGd2[SiO3]4F2

This work reports the luminescence spectra and application of novel Eu3+-doped Na2MgGd2[SiO3]4F2 phosphor. The X-ray powder diffraction confirmed the pure phase formation of the samples with the monoclinic space group P21/c (No:14). The phosphors demonstrated efficient red emission at 613 nm from the electric dipole transitions 5D0→7F2. The optimal doping concentration was found to be approximately 25 mol%. Na2MgGd2[SiO3]4F2:0.25Eu3+ exhibits a high quantum efficiency (QE) of 57 % with excellent thermal stability and pure chromaticity. Red- and the white light-emitting diode devices were packaged using InGaN chips and Na2MgGd2[SiO3]4F2:0.25Eu3+. The fabricated WLED has CIE coordinates of (x = 0.33, y = 0.34), which are very close to the white point in the National Television System Committee (x = 0.33, y = 0.33). The color rendering index (CRI, Ra) and correlated color temperature (CCT) of the WLED are 91 and 4400 K, respectively. The results show that as a red luminescent phosphor, it is a potential candidate for the preparation of near-UV/blue InGaN-based WLEDs.

Pure white emission full thermally activated delayed fluorescence organic light emitting diode with a supplementary emission layer

In addition to efficiency and lifetime, spectral stability, high color rendering index (CRI), and the Commission Internationale de l’Eclairag (CIE) coordinate close to the equi-energy white point (0.33, 0.33) are also important parameters for the development of white organic light emitting diodes (WOLEDs). However, how to realize these advantages at the same time is a challenge. In this paper, a series of white devices based on complementary color full thermally activated delayed fluorescence (full-TADF) emitters were fabricated with the aim to obtain WOLEDs with high color rendering index and CIE coordinate near the equi-energy white point. Through optimizing the doping concentration of the emitters, adding a supplementary emission layer, modifying the thickness of the main emission layer and the supplementary emission layer, the best device displays the CIE coordinates of (0.34, 0.35) and the CRI of 86, exhibiting good white emission. The results in this paper may provide a feasible method for realizing complementary color full-TADF WOLEDs with pure white emission.

Extraction of Crop Row Navigation Lines for Soybean Seedlings Based on Calculation of Average Pixel Point Coordinates

The extraction of navigation lines is a crucial aspect in the field autopilot system for intelligent agricultural equipment. Given that soybean seedlings are small, and straw can be found in certain Northeast China soybean fields, accurately obtaining feature points and extracting navigation lines during the soybean seedling stage poses numerous challenges. To solve the above problems, this paper proposes a method of extracting navigation lines based on the average coordinate feature points of pixel points in the bean seedling belt according to the calculation of the average coordinate. In this study, the soybean seedling was chosen as the research subject, and the Hue, Saturation, Value (HSV) colour model was employed in conjunction with the maximum interclass variance (OTSU) method for RGB image segmentation. To extract soybean seedling bands, a novel approach of framing binarised image contours by drawing external rectangles and calculating average coordinates of white pixel points as feature points was proposed. The feature points were normalised, and then the improved adaptive DBSCAN clustering method was used to cluster the feature points. The least squares method was used to fit the centre line of the crops and the navigation line, and the results showed that the average distance deviation and the average angle deviation of the proposed algorithm were 7.38 and 0.32. The fitted navigation line achieved an accuracy of 96.77%, meeting the requirements for extracting navigation lines in intelligent agricultural machinery equipment for soybean inter-row cultivation. This provides a theoretical foundation for realising automatic driving of intelligent agricultural machinery in the field.

Metabolomics research on treatment of primary liver cancer with Cortex Juglandis Mandshuricae on LC-MS/MS technology

Diethylnitrosamine (DEN) was applied to create the primary liver cancer (PLC) animal model. In the study, the normal group, model group, cyclophosphamide (CTX) group, Cortex Juglandis Mandshuricae (CJM) extract group, myricetin group and myricitrin group were divided. LC-MS/MS technology was applied to determine the metabolites of liver tissue samples from different locations (nodular and non-nodular parts of liver tissue) in each group of rats. Through metabolomics research, the connection and difference of anti-PLC induced by the CJM extract, myricetin and myricitrin was analyzed. The surface of the liver tissues of rats in the model group was rough, dimly colored, inelastic, on which there were scattered gray white cancer nodules and blood stasis points. The number of cancer nodules was significantly reduced, and the degree of cell malignancy was low, but there were some inflammatory cell infiltrations, necrosis area and karyokinesis in the CJM extract group, myricetin group, myricitrin group and CTX group. The result of metabolic research indicated that 45 potential biomarkers of the PLC were found, as gamma-aminoisobutyrate, taurochenodeoxycholate, xanthurenic acid, etc. There were 22 differential metabolites in the CTX group, 16 differential metabolites in the CJM extract group, 14 differential metabolites in the myricetin group, 14 differential metabolites in the myricitrin group.

58‐1: A Novel On‐line, Fast Color Correction by Machine Learnings

A new efficient color correction method, utilizing neural network models, is proposed by this study for OLED panels in production, offering a transformative approach to achieve accurate and rapid color calibration. Utilizing transfer learning with a limited dataset, it creates color conversion matrices for AI‐driven color correction. The process involves selecting a similar baseline model from prior batches with a ΔE00 below 1, then refining it using a representative dataset. This model corrects white point and overall color, achieving a ΔE00 less than 2. It corrects 300 data points in less than 4 seconds, demonstrating both speed and accuracy.

P‐214: TADF/Fluorescent Hybrid WOLED Device with Adjustable Color Temperature

Although the tandem WOLED have the potential of high efficiency and long lifetime, the high voltage of tandem structure usually limits its application inAR/VR products. To achieve low voltage WOLED, it is necessary to develop single structure. Most of the reported single WOLED with the use of TADF materials show a relatively large CIE coordinates. In this work, we use the combination of blue fluorescence and yellow TADF materials with a 1‐2 nm p‐type interlayer material between them. The energy is transferred from blue fluorescence to TADF. And finally, the single WOLED with tunable color temperature was realized. The CIE coordinates can be tuned from the warm white point of (0.313, 0.323) to the cold white point of (0.285, 0.279). The roll‐off of efficiency from 240 nit to 3000 nit is lower than 10%, and the lifetime (LT95) can reach 1300 h at 1000 nit.

8‐2: Distinguished Paper: Adaptive Display White Point under Various Ambient Conditions

Chromatic adaptation is an important mechanism in the human visual system, allowing a relative constant color appearance under different lighting conditions, in terms of light level and color. Technologies have been developed to adjust the display white point according to the ambient light color, but did not consider the ambient light level. This study was designed based on a recent study to reveal the necessity to consider ambient light level and display luminance together, which affects the viewing mode, when adjusting the adaptive display white point.

Enhancing T1 signal of normal-appearing white matter with divided subtracted inversion recovery: A pilot study in mild traumatic brain injury.

Magnetic resonance imaging (MRI) and cognitive profiles in patients with mild traumatic brain injury (mTBI) are often discordant. Conventional MRI seldom captures the full extent of pathological changes in the normal-appearing white matter (NAWM). The divided subtracted inversion recovery (dSIR) technique may enhance T1 differences in NAWM, making them easily visible. We aimed to implement dSIR on a clinical scanner and tested results in mTBI patients. To produce dSIR images, Inversion Recovery-Turbo Spin Echo sequences were modified using six different inversion times (TI) on a 3-T scanner in healthy participants and patients with mTBI. The multiple TIs determined normal white (TIshort) and gray matter (TIlong) nulling points in healthy subjects, which were used to create dSIR images. In one patient, the protocol was repeated at 3 months to identify changes after rehabilitation. Diffusion tensor imaging (DTI)-derived mean diffusivity (MD) and fractional anisotropy (FA) maps were aligned to dSIR images to ensure that signal was not artefactual. Ten healthy participants (five females; age 24 ± 3 [95% CI: 21, 26] years) were included. TIshort and TIlong were set at 450 and 750 ms, respectively. In both patients (one male, age 17 years; one female, age 14 years), dSIR images revealed areas with increased T1 in the NAWM not visible on conventional MRI. dSIR-based hyperintensities corresponded to elevated MD and reduced FA. Substantial changes were found at follow-up with improvement in DTI-based parameters. dSIR images enhance subtle changes in the NAWM of patients with mTBI by amplifying their intrinsic T1 signal.

Hybrid Semiconductor Wafer Inspection Framework via Autonomous Data Annotation

Abstract In smart manufacturing, semiconductors play an indispensable role in collecting, processing, and analyzing data, ultimately enabling more agile and productive operations. Given the foundational importance of wafers, the purity of a wafer is essential to maintain the integrity of the overall semiconductor fabrication. This study proposes a novel automated visual inspection (AVI) framework for scrutinizing semiconductor wafers from scratch, capable of identifying defective wafers and pinpointing the location of defects through autonomous data annotation. Initially, this proposed methodology leveraged a texture analysis method known as gray-level co-occurrence matrix (GLCM) that categorized wafer images—captured via a stroboscopic imaging system—into distinct scenarios for high- and low-resolution wafer images. GLCM approaches further allowed for a complete separation of low-resolution wafer images into defective and normal wafer images, as well as the extraction of defect images from defective low-resolution wafer images, which were used for training a convolutional neural network (CNN) model. Consequently, the CNN model excelled in localizing defects on defective low-resolution wafer images, achieving an F1 score—the harmonic mean of precision and recall metrics—exceeding 90.1%. In high-resolution wafer images, a background subtraction technique represented defects as clusters of white points. The quantity of these white points determined the defectiveness and pinpointed locations of defects on high-resolution wafer images. Lastly, the CNN implementation further enhanced performance, robustness, and consistency irrespective of variations in the ratio of white point clusters. This technique demonstrated accuracy in localizing defects on high-resolution wafer images, yielding an F1 score greater than 99.3%.

Adaptive display white point under various ambient conditions

AbstractDisplay technologies have been developed to adjust the display brightness and color under different viewing conditions, providing better viewing experiences to users. Solutions have been proposed to adjust the display white point according to the ambient light condition, which roots into the underlying chromatic adaptation mechanism in the human visual system. This study was carefully designed to reveal the necessity to consider the ambient light level and display luminance together, which affects the viewing mode, when adjusting the adaptive display white point. The results clearly suggested that when the display luminance was greater than the ambient light diffuse white luminance, the display was viewed in the self‐luminous mode and the display white point was not significantly affected by the ambient light chromaticities. In contrast, when the display luminance was lower than the ambient light diffuse white luminance, the display was viewed in the surface mode and the ambient light chromaticities had a significant effect on the display white point, especially when the surround ratio was high.

Shunted piezoelectric patch adaptive vibration absorber set to maximise electric power absorption: A comparison between parallel and series RL-shunts

This paper presents a comparative study on two types of shunted piezoelectric patch adaptive vibration absorbers, which can be bonded in batches on thin-walled structures to control the broad-band resonant response of low order flexural modes. The self-contained control units are formed by a thin piezoelectric patch connected either to a series or to a parallel resistive-inductive (RL) network. The two components of the shunt are adapted online in such a way as to maximise the time-averaged electric power absorbed by the shunt, which corresponds to minimising the time-averaged total flexural response of the hosting structure. The study considers a practical demonstrator formed by a thin rectangular plate with five piezoelectric patches connected to digital RL-shunts, which is excited in bending by a stationary white noise point force. The aim of the paper is to contrast the tuning and vibration control properties of the series and parallel RL shunts. More specifically, the online implementation of a recursive two-paths tuning strategy along R-constant and L-constant paths with an extremum seeking gradient search algorithm is analysed first for the two types of shunts. Then, the vibration control performance produced by the two types of shunts is investigated for the case where they are tuned to control the resonant response of the first flexural mode of the plate.

Development of compact-modulated absorption/emission technique towards micro-gravity sooting flame measurements

To meet the experimental physical limitations on Chinese Space Station (CSS), three compact-modulated absorption/emission (CMAE) implementations are miniaturized progressively from original MAE layout, which are investigated as potential options for simultaneous soot temperature and volume fraction measurements in the axis-symmetric flames. Contrasted with the original MAE technique, a white LED point light source (diameter of ϕ = 8 mm) and a white LED planar light source (rectangle of 200 × 120 mm2) in turns replaces the laser source, by which the light beam homogeneous implementation is significantly simplified. Moreover, a 3-CMOS prism-based camera enables simultaneously recording flame two color radiations that reduces the detecting complexity. It is found that backlight beam intensity should be more than 2.5 times the flame radiation intensity to avoid abnormal extinction coefficient on the flame edge in this configuration. Moreover, the robustness and consistency of the three CMAEs measurements are validated with a standard Santoro’s flame, and low average standard deviation ranges of ±0.04∼±0.06 ppm and ±65.0∼± 96.3 K for soot volume fraction and temperature respectively is evaluated from error propagation assessment. As such, the proposed CMAE-2 and CMAE-3 layouts are promising candidates for high-fidelity flame soot parameters measurements under limited space, weight and power supply on CSS.

Effective cross-sensor color constancy using a dual-mapping strategy.

Deep neural networks (DNNs) have been widely used for illuminant estimation, which commonly requires great efforts to collect sensor-specific data. In this paper, we propose a dual-mapping strategy-the DMCC method. It only requires the white points captured by the training and testing sensors under a D65 condition to reconstruct the image and illuminant data, and then maps the reconstructed image into sparse features. These features, together with the reconstructed illuminants, were used to train a lightweight multi-layer perceptron (MLP) model, which can be directly used to estimate the illuminant for the testing sensor. The proposed model was found to have performance comparable to other state-of-the-art methods, based on the three available datasets. Moreover, the smaller number of parameters, faster speed, and not requiring data collection using the testing sensor make it ready for practical deployment. This paper is an extension of Yue and Wei [Color and Imaging Conference (2023)], with more detailed results, analyses, and discussions.

Spectroscopic investigation of K5La(MoO4)4:Sm3+ red phosphor with excellent thermal stability and color purity for white LEDs

In this study, a series of innovative red-emitting Sm3+-doped K5La(MoO4)4 phosphors were synthesized using the solid-state reaction method. The X-ray powder diffraction patterns and Rietveld refinement confirmed the single-phase structure of the synthesized K5La(MoO4)4:Sm3+ samples with trigonal system (space group R3‾m (#166)). The phosphors demonstrated a strong red emission at 644 nm, corresponding to the electric dipole transition 4G5/2 → 6H9/2 of Sm3+ ions. The optimal doping concentration for K5La(1-x) (MoO4)4:xSm3+ was found to be approximately 5 mol%. The temperature-dependent emission of phosphors was examined and found that the luminescence intensity remained at 86 % even at 480 K, showing the exceptional thermal stability of this material. K5La(1-x) (MoO4)4:xSm3+ phosphors displayed remarkable color stability with chromaticity coordinates falling within the red region in 1931 CIE diagram. K5La(MoO4)4:5 mol%Sm3+ exhibited a high color purity of 99.9 % and internal quantum efficiency (IQE) was measured as 66.8 %. Light-emitting diodes (LEDs) were constructed using InGaN chips and the synthesized red phosphors. The chromaticity coordinates of the fabricated w-LED (white light-emitting diode) were (0.330, 0.351), closely resembling the typical white point of the National Television System Committee (NTSC) at (0.333, 0.333). The color rendering index (CRI, Ra) and correlated color temperature (CCT) of w-LED were 87 and 5627 K. These findings strongly suggest the potential use of K5La(MoO4)4:Sm3+ phosphors as red phosphors in LEDs.

Balanced multi-scale target score network for ceramic tile surface defect detection

Ceramic tiles, as a prevalent building material, exhibit a wide variety of types and high demand. Traditional manual inspection methods relying on human visual observation suffer from low efficiency and unreliable accuracy. Current automated detection methods mostly rely on traditional image processing techniques for feature extraction, followed by machine learning-based classification. However, faced with the diversity of tile types and defect categories, fine-tuning and deployment processes require significant human and material resources, while detection efficiency remains limited. In this study, we first construct a high-resolution dataset for studying surface defects in ceramic tiles (CT surface defects dataset), encompassing multiple batches and various patterns of tiles. Subsequently, data analysis is conducted to address the scale and quantity differences in defect distribution. We propose an improved approach by introducing a content-aware feature recombination method and a dynamic attention mechanism to enhance the classical single-stage object detection algorithm YOLOv5. These enhancements aim to reduce information loss in features and enhance the expression of multi-scale features. Furthermore, we design a loss function that mitigates score differences for multi-scale defects. The proposed approach mitigates the discrepancy in contribution among different scale targets caused by imbalanced quantities. It effectively prevents the model from excessively favoring a specific scale target during the learning process. Experimental results demonstrate the superior accuracy and efficiency of our detection method.Compared to the baseline network YOLOv5, our approach achieved improvements of 4.9% in AP (Average Precision), 6% in APs (small-scale objects), and 8% in APl (large-scale objects). Furthermore, we achieved a 3.9% improvement in detecting white point defects, which are most affected by small-scale objects, and a 4.1% improvement in detecting discolored spot defect, which are most affected by class imbalance.

Effect of viewing environments on perceived display neutral point

In this study, the influences of ambient chromaticity, ambient luminance, and display luminance on the perceived neutral point of a display were systematically investigated using 25 experimental settings. The results show that the surround ratio, i.e., the ratio of the ambient luminance to the display luminance, had a greater effect on the display neutral point perception than the absolute intensity of each factor. As the surround ratio decreased, indicating that the display luminance was higher than the ambient luminance, the perceived display neutral point changed from the adapted white to the neutral point in the darkroom condition (corresponding to a surround ratio of zero) at approximately 7,200 K. When the surround ratio exceeded 1.0, the neutral point of the display gradually shifted toward specific levels. The correlated color temperatures of the perceived display neutral points converged to 5,000 and 5,900 K under ambient lighting conditions of 3,000 and 5,000 K, respectively.

Identification method for dental alloy type using a cosine similarity program: A preliminary investigation.

Although dental evidence is frequently used for the identification of unidentified persons, information about the many types of alloys used in prosthetics is not utilized. If the type of alloy can be identified from a small amount of material, the scope of the search could be narrowed. In this experiment, a method was investigated for identifying the alloy type using 3 kinds of cutting points (a white point and 2 types of silicone points). Wavelength-dispersive X-ray spectroscopy (WDS) was used for elemental analysis. The elements were translated into multidimensional vectors, and the cosine similarity was calculated to compare vectors of the WDS results and vectors of the official data of alloys. According to the results, cosine similarity showed a concordance of more than 0.8. The developed program is expected to be useful as a method for identifying alloy types using only a small amount of grinding dust.

Poster Session: Chromatic Adaptation to Heterochromatic Illumination.

Heterochromatic viewing enviroments-where scenes are illuminated by two or more colors of light-are a common tool for experiments studying chromatic adaptation and color (in)constancy. This study presents a new method for separating sensory (retina-based) chromatic adaptation from cognitive mechanisms in a heterochromatic viewing environment. Using a large, bipartite light booth lit by two separate 7-channel LED systems, observers were adapted to uniform and mixed illuminations of simulated illuminant A, illuminant D65, and 12000 K daylight. A psychophysical staircase method determined observers' white points and their state of sensory adaptation along the daylight and Planckian loci under each heterochromatic or single-color lighting condition. Under heterochromatic conditions, observers' state of chromatic adaptation fell in between the points of chromatic adaptation when adapted to each individual light source, although there was significant variation between observers. These results suggest that observers' white points should be individually determined for studies of color perception in heterochromatic environments using methods similar to those used in this study. Further research will then allow us to model how cognitive discounting of the illumination color sits on top of the sensory adaptation measured here.

Single Pixel Spectral Color Constancy

Color constancy is still one of the biggest challenges in camera color processing. Convolutional neural networks have been able to improve the situation but there are still problems in many conditions, especially in scenes where a single color is dominating. In this work, we approach the problem from a slightly different setting. What if we could have some other information than the raw RGB image data. What kind of information would help to bring significant improvements while still be feasible in a mobile device. These questions sparked an idea for a novel approach for computational color constancy. Instead of raw RGB images used by the existing algorithms to estimate the scene white points, our approach is based on the scene’s average color spectra-single pixel spectral measurement. We show that as few as 10–14 spectral channels are sufficient. Notably, the sensor output has five orders of magnitude less data than in raw RGB images of a 10MPix camera. The spectral sensor captures the “spectral fingerprints” of different light sources and the illuminant white point can be accurately estimated by a standard regressor. The regressor can be trained with generated measurements using the existing RGB color constancy datasets. For this purpose, we propose a spectral data generation pipeline that can be used if the dataset camera model is known and thus its spectral characterization can be obtained. To verify the results with real data, we collected a real spectral dataset with a commercial spectrometer. On all datasets the proposed Single Pixel Spectral Color Constancy obtains the highest accuracy in the both single and cross-dataset experiments. The method is particularly effective for the difficult scenes for which the average improvements are 40–70% compared to state-of-the-arts. The approach can be extended to multi-illuminant case for which the experimental results also provide promising results.