Color Distribution Research Articles

Enhancing Accuracy of Flame Equivalence Ratio Measurements: An Attention-Based Convolutional Neural Network Approach for Overcoming Limitations in Traditional Color Modeling

This paper addresses the inherent limitations in traditional color modeling techniques for measuring the flame equivalence ratio (Φ), particularly focusing on the subjectivity involved in threshold settings and the challenges posed by uneven 2D color distribution. To overcome these issues, this study introduces an attention-based convolutional neural network (ACN) model, a novel approach that transcends the conventional reliance on B/G color features (Tf). The ACN model leverages adaptive feature extraction, augmented by a spatial attention mechanism, to more effectively analyze flame images. By amplifying key features, autonomously minimizing background noise, and standardizing variations in color distribution, the ACN model in this experiment achieved a prediction accuracy of 99%, with a 76% reduction in error rate compared to the original model, significantly improving the accuracy and objectivity of flame Φ measurement. This method marks a substantial development in the precision and reliability of flame analysis.

Color Ranges and Distribution of Human Teeth: A Prospective Clinical Study.

This study investigated the in vivo color range of human teeth using a research-grade noncontact spectroradiometer, analyzing the effects of gender, age, ethnicity, and lifestyle factors, including diet, smoking, and oral hygiene. A total of 1004 participants were recruited at two research sites and stratified by gender, age, and ethnicity, and data on their dietary and oral habits were collected. Noninvasive color measurements of an upper central incisor were performed using a spectroradiometer and a fiber-coupled Xe-Arc light source. Color differences were computed using the CIELAB and CIEDE2000 color difference formulas, statistically analyzed, and interpreted through comparisons with 50:50% perceptibility (PT) and acceptability (AT) thresholds for dentistry. CIELAB and CIEDE2000 color coordinate values varied significantly. Female teeth appeared lighter and less yellow than men's. Age correlated with darker, more chromatic teeth, stabilizing only after Age 46. Significant ethnic differences were observed, particularly between African-American and Asian participants. Coffee consumption impacted teeth yellowness and chromaticity, while tea had no significant effect. Frequent tooth brushing led to lighter teeth, and tooth whitening considerably influenced color, emphasizing the effect of cosmetic dental treatments. Smoking showed minimal impact, with slight discoloration noted among light smokers compared to nonsmokers. Color coordinate values by gender, age, and ethnicity exhibited statistically significant differences and, in most cases, noticeable color differences. With exceptions, the dietary/oral habits of the patient had a significant impact on the color of human teeth. The findings from this study provide detailed information and understanding of the color range and distribution of human teeth, which can help enhance the esthetic outcome of dental care and, consequently, the patient's satisfaction.

Virtual cleaning of sooty mural hyperspectral images using the LIME model and improved dark channel prior

Murals, as important carriers of cultural heritage and historical records, showcase artistic, aesthetic, social, and political significance. In ancient times, religious activities such as burning incense and candles in temples led to many murals being polluted by soot, causing them to darken, lose details, and, in severe cases, completely blacken. As a result, the development of efficient virtual cleaning methods has become a key strategy for addressing this issue. In this study, we use synthetic true colour and false colour images in different bands of the hyperspectral spectrum, and use a guided filter fusion technique to fuse these two images into a new image of the sooty mural. Through analyzing the histograms and colour distribution scatterplots of the synthetic sooty mural images, we observed significant similarities to low-luminance images. To enhance the synthesized murals, we applied the LIME model. In addition, comparisons of the histograms and colour distribution scatterplots of the enhanced sooty mural images with those of haze images revealed notable similarities. Therefore, we applied the dark channel prior algorithm to remove soot from the mural images. Considering that soot particles are larger than haze particles, we introduced guided filtering to refine the transmission map and created a nonlinear transformation function to enhance its details. In terms of both visual perception and quantitative analysis, the proposed method significantly outperforms previous methods in the virtual cleaning of sooty murals. This technology can not only restore the colours and details of murals but also provide new clues for subsequent mural studies, allowing people to once again appreciate the true beauty of the murals.

Imprints of interaction processes in the globular cluster system of NGC 3640

We present a wide-field study of the globular cluster systems (GCS) of the elliptical galaxy NGC 3640 and its companion NGC 3641, based on observations from Gemini Multi-Object Spectrograph/Gemini using g’r’i’ filters. NGC 3640 is a shell galaxy which presents a complex morphology, which previous studies have indicated as the sign of a recent ‘dry’ merger, although whether its nearest neighbour could have influenced these substructures remains an open question. In this work, we trace the spatial distribution of the globular clusters (GCs) as well as their colour distribution, finding a potential bridge of red (metal-rich) GCs that connects NGC 3640 to its less massive companion, and signs that the blue (metal-poor) GCs were spatially disturbed by the event that created the shells. While NGC 3640 presents a typical bimodal colour distribution, the GCS attributed to NGC 3641 appears unimodal, with most GCs presenting an intermediate colour in comparison to those closer to its companion.

Comparison of cycloplegic refraction in children with different iris colour categories. A cross- sectional survey

Objective: To compare the cycloplegic refraction in children with different iris colour categories and age groups. Methods: The cross-sectional study was conducted from December 2022 to June 2023 at the Eye Clinic of Sehat Medical Complex, Hanjarwal, Lahore, and Khizar Eye Centre, Lahore, Pakistan, and comprised hyperopic children aged 5-12 years of either gender. Data regarding age, gender, iris colour, auto-refraction and retinoscopy before and after cycloplegic refraction was collected using a structured proforma. Data was analysed using SPSS 21. Results: Of the 139 subjects, 73(52.5%) were males and 60(47.5%) were females. There were 79(56.8%) subjects aged 5-8 years and 60(43.2%) aged 9-12 years. The iris colour distribution was 23(16.5%) light, 80(57.6%) medium and 36(25.9%) dark, with a mean visual acuity of 0.7±0.6. There was a significant difference in non-cycloplegic and cycloplegic refraction for different iris colours and age groups (p<0.05). Conclusion: Children with light iris colour accommodated more and needed a low concentration of cyclopentolate compared to those with medium and dark iris colours. More accommodation was noted among children aged 9-12 years. Key Words: Cycloplegic refraction, Cyclopentolate, Hyperopia, Iris, Ocular refraction, Retinoscopy.

A Study on Enhancing the Visual Fidelity of Aviation Simulators Using WGAN-GP for Remote Sensing Image Color Correction

When implementing outside-the-window (OTW) visuals in aviation tactical simulators, maintaining terrain image color consistency is critical for enhancing pilot immersion and focus. However, due to various environmental factors, inconsistent image colors in terrain can cause visual confusion and diminish realism. To address these issues, a color correction technique based on a Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP) is proposed. The proposed WGAN-GP model utilizes multi-scale feature extraction and Wasserstein distance to effectively measure and adjust the color distribution difference between the input image and the reference image. This approach can preserve the texture and structural characteristics of the image while maintaining color consistency. In particular, by converting Bands 2, 3, and 4 of the BigEarthNet-S2 dataset into RGB images as the reference image and preprocessing the reference image to serve as the input image, it is demonstrated that the proposed WGAN-GP model can handle large-scale remote sensing images containing various lighting conditions and color differences. The experimental results showed that the proposed WGAN-GP model outperformed traditional methods, such as histogram matching and color transfer, and was effective in reflecting the style of the reference image to the target image while maintaining the structural elements of the target image during the training process. Quantitative analysis demonstrated that the mid-stage model achieved a PSNR of 28.93 dB and an SSIM of 0.7116, which significantly outperforms traditional methods. Furthermore, the LPIPS score was reduced to 0.3978, indicating improved perceptual similarity. This approach can contribute to improving the visual elements of the simulator to enhance pilot immersion and has the potential to significantly reduce time and costs compared to the manual methods currently used by the Republic of Korea Air Force.

DBSF-Net: Infrared Image Colorization Based on the Generative Adversarial Model with Dual-Branch Feature Extraction and Spatial-Frequency-Domain Discrimination

Thermal infrared cameras can image stably in complex scenes such as night, rain, snow, and dense fog. Still, humans are more sensitive to visual colors, so there is an urgent need to convert infrared images into color images in areas such as assisted driving. This paper studies a colorization method for infrared images based on a generative adversarial model. The proposed dual-branch feature extraction network ensures the stability of the content and structure of the generated visible light image; the proposed discrimination strategy combining spatial and frequency domain hybrid constraints effectively improves the problem of undersaturated coloring and the loss of texture details in the edge area of the generated visible light image. The comparative experiment of the public infrared visible light paired data set shows that the algorithm proposed in this paper has achieved the best performance in maintaining the consistency of the content structure of the generated image, restoring the image color distribution, and restoring the image texture details.

Optical Image Processing using Eulerian Amplification

Recent advancements in digital photography, particularly through mobile phone cameras, microscopes, and satellite imaging, have made high-resolution image capture increasingly accessible. However, these captured images often contain subtle changes in color resolution and density that are challenging to observe with the naked eye. This study explores the application of Eulerian amplification as a method to detect and enhance such small-amplitude variations, making them visible for improved analysis. Unlike traditional approaches, Eulerian methods are particularly effective for processing smooth structures and high-quality printed materials where minor amplifications in color can reveal significant grading details. Using a pixel-by-pixel Eulerian path analysis, this method allows for a detailed comparison of color intensity values on a fine 8-bit scale, which ranges from 0 to 255. Through this analysis, color distribution patterns are visualized across the spatial structure of the image, which is particularly beneficial for identifying specific variations in quality in printed materials, such as highly graded cards. To manage large image structures, spatial decomposition using a multi-level Gaussian pyramid technique is employed. By applying temporal filtering within select frequency bands (0.4–4 Hz) at a coarse pyramid level, the algorithm effectively pools spatial data, enabling the detection of color density shifts that may indicate image defects. The amplified image data is further processed using a classifier neural network, which provides high sensitivity and specificity in detecting edge defects, image centering issues, scuffs, and breakages. The system demonstrates promising results in identifying true positives while maintaining low false-negative rates, thus confirming the reliability of deep machine learning algorithms in high-sensitivity defect detection. This paper presents the significance of Eulerian amplification in optical image processing, offering a robust tool for precise, automated defect detection across a variety of high-resolution image types.

Regularity through randomness: Bioinspired quasi-amorphous photonic structures for multilevel information encryption

The biological world has produced a wealth of complex photonic materials offering abundant design inspirations. However, creating these intricate photonic structures intertwining order, disorder, and hierarchical arrangements remains challenging. Achieving this necessitates nano-fabrication technologies capable of integrating intended macroscopic properties while accommodating microscopic variability or randomness, akin to the operational principles observed in biological organisms. Here, we present quasi-amorphous photonic structure (QAPS) patterns with regulated sophisticated visual effects through hierarchically distributions of photonic elements with engineered randomness. Enabled by an infiltration-assisted (IFAST) inkjet printing method, the visual appearances of QAPS patterns are precisely controlled by collective harnessing of nanoscale resonant scattering of colloids, mesoscale interferences, and macroscale light transporting. The QAPS patterns exhibit isotropic diffuse colors, unprecedented iridescence and enable multichannel encrypted information that can be selectively identified using specific filters at particular specular illumination angles. Additionally, the intricate infiltration fields confer high adjustability in colloidal assembly, offering sophisticated packing geometries and color distributions at the microscale, which can serve as physical unclonable security features. The exceptional structural complexity and optical versatility of QAPSs enable the integration of multilevel security features within a single system, providing a promising roadmap to achieve larger information capacity, multichannel cryptography, and enhanced encryption levels.

Effects of Agricultural Land Use on Desert Soil Classification in Holy Karbala Governorate

This study was conducted to evaluate physical, chemical, and morphological features to classify soils at the subgroup level. The research area, located west of Karbala, consists of three locations, each comprising pedons in both cultivated and uncultivated lands. GPS coordinates were recorded, and morphological descriptions of pedon horizons were made in accordance with the American Soil Survey Manual. This study investigates the effect of agricultural land use on the classification of desert soils in the Holy Karbala Governorate. The results revealed that the dry climate caused diversity in the morphological features of the soils, mainly in horizon type, thickness, and arrangement. Agricultural usage had an impact on diagnostic horizons, particularly the gypsic horizon, and features such as soil color, structure, organic matter, carbonate minerals, gypsum, and root distribution. However, there was no substantial impact on soil texture development, and soils did not show a consistent pattern of soil separation distribution with depth, indicating weak pedogenic processes. The most common texture classes were loamy sand, sandy loam, and sand, with sand contents ranged from 902.08 to 574.12 g kg. Soil bulk density differed from 1.67 to 1.30 Mg m³, with lower values in farmed areas. Chemical properties were influenced, with soil pH ranging from 8.36 to 7.54, electrical conductivity (EC) from 5.46 to 2.03 dS m, cation exchange capacity (CEC) from 15.25 to 2.05 meq.100g, organic matter from 43.51 to 1.18 g kg, carbonate minerals from 461.18 to 174.06 g kg, and calcium sulfate from 182 to 21 g kg. The soils were classed as Aridisols because they were found in a dry desert with an Aridic moisture regime. The presence of distinctive saline layers such as Calcic and Gypsic was discovered, resulting in the classification of cultivated soils as Typic Haplocalcids and uncultivated lands as Typic Calcigypsids.

Multiple Multicolored 3D Polarization Knots Arranged along Light Propagation.

Polarization and color play essential roles in understanding optical phenomena and practical applications. Customized three-dimensional (3D) light fields, characterized by specific polarization and color distributions, have garnered growing interest owing to their unique optical attributes and expanded capacity for information encoding. To align with the ongoing trend of compactness and integration, it is desirable to develop lightweight optical elements that can simultaneously control polarization and color in 3D space. Although engineering longitudinally variable 3D optical structures with predesigned color and polarization information can add more degrees of freedom and additional capacity for information encoding, it has not been reported. We propose a metasurface approach to generating multiple 3D polarization knots along the light propagation direction. Each knot features two colors and an engineered 3D polarization profile. Different multicolored 3D polarization knots are obtained by controlling the observation region along the light propagation. Our approach simultaneously combines polarization, color, and longitudinal control in 3D environment, offering extra degrees of freedom for engineering complex vector beams. The unique properties of the developed metadevices, together with the design flexibility and compactness of metasurface, pave the way for polarization systems with small volumes applicable to some areas such as complex structured beams and encryption.

Color distribution learning modulates saccade endpoints: a study of the global effect

Color distribution learning modulates saccade endpoints: a study of the global effect

Addressing cities’ color issues and planning urban colors with regional features to preserve the history and culture of cities: the case of Suzhou, Wuxi, and Changzhou (China)

ABSTRACT Although there are many remarkable examples of color traditions from different parts of the world, many cities still face color-related issues, such as lack of regionality and clutter. Since the color issues of different cities vary, the solutions must also be different. This paper examines the old urban areas of Suzhou, Wuxi, and Changzhou in China as a case study to investigate how to solve urban color problems and shape the architectural color with regional characteristics. By exploring the spatial distribution of color categories and the interval distribution of color attribute values, this paper finds that the increase in colored buildings (especially along the main roads) and the excessive chromaticity of new buildings affect the regionality of urban colors. Therefore, we propose restoring urban color by establishing color zoning and controlling chromaticity to increase cultural diversity, promote economic vitality, and enhance people’s sense of belonging. The planning of urban color and the establishment of color patterns with regional characteristics are of positive significance for the development of urban history, culture, and habitat.

Barred active galactic nucleus galaxies in paired systems: Exploring the impact on nuclear activity

To unveil the influence of galaxy-galaxy interactions on the material transport driven by galactic bars toward the central regions of active galactic nucleus (AGN) galaxies, and to assess the efficiency of the combined mechanisms of interactions and bars in fueling massive black holes, we meticulously examine barred active galaxies in paired systems. Our study focuses on barred AGN galaxies in pairs with projected separations of $r_ p \,kpc $ and relative radial velocities of $ V< 500 \,km $ within $z<0.1$, identified by the Sloan Digital Sky Survey (SDSS). To quantify the impact of interactions on material transport by galactic bars, we also constructed a suitable control sample of barred active galaxies without paired companions, matched in redshift, absolute r-band magnitude, stellar mass, color, and stellar age distributions. Additionally, we calculated the structural characteristics of galactic bars through two-dimensional image modeling, considering that bars exhibit a wide range of shapes and sizes, which may influence their ability to channel material. From this study, we clearly found that nuclear activity (derived from the $Lum OIII $) increases as the projected separations between galaxy pair members decrease. Notably, barred AGN galaxies in close pairs ($r_p 25 kpc $) exhibit significantly higher nuclear activity compared to galaxies in the control sample. Additionally, barred galaxies with a close pair companion show enhanced nuclear activity across all ranges of luminosity, stellar mass, and color. We also found that barred AGN galaxies with longer bar structures exhibit more efficient nuclear activity compared to those with shorter bars. This trend is especially pronounced in barred AGN galaxies within close pair systems, which show a significant excess of high $Lum OIII $ values. Furthermore, we examined the central nuclear activity in barred AGNs undergoing major and minor interactions. Our findings show a clear escalation in nuclear activity as the pair projected separations decrease, particularly pronounced in major systems. Additionally, nuclear activity distributions in barred AGN samples within major and minor pairs exhibit similar trends. However, a significant deviation occurs among barred AGN galaxies in close pair systems within major interactions, showing a substantial excess of high $Lum OIII $ values. This result is also reflected in the analysis of the accretion strength onto central black holes. These findings indicate that external perturbations from a nearby galaxy companion can influence gas flows induced by galactic bars, leading to increased nuclear activity in barred AGN galaxies within pair systems. Thus, the coexistence of both — bars and interactions — significantly amplifies central nuclear activity, thereby influencing the accretion processes onto massive black holes.

Color Analysis of Brocade from the 4th to 8th Centuries Driven by Image-Based Matching Network Modeling

To achieve the color matching rules for the textiles discovered during Silk Road excavations between the 4th and 8th centuries, this research proposed an image-based matching network modeling method. The Silk Road facilitated trade and cultural exchange between the East and West, and the textiles found along the way depict the development of fabrics in a color scheme with great cultural significance. A total of 165 images with brocade patterns were collected from a book with a detailed description of the Western influences on textiles along the Silk Road. Two different clustering methods, including the K-means clustering method and octree quantization approach, were used to extract the primary and secondary colors. By combining the HSV color space with the PCCS color system, the color distribution was analyzed to discover the features of representative color patterns. The co-occurrence relationship of the auxiliary colors was explored using the Apriori algorithm, and a total of eight association rules were established. The results showed that the K-means clustering algorithm can show a better effect of color classification to obtain three primary colors and nine secondary colors. The matching mechanism with a visualized network model was also proposed, which showed that reddish-yellow tones are the main colors in the brocade patterns, and the light and soft tones separately account for 27% and 20%. Beige and brown are the most common colorways, with a confidence level of 47%. One style of brocade pattern was used to demonstrate different appearances within various color networks, which could be applied to 3D virtual fitting. This image-based matching network modeling approach makes the color matching schemes visible, and can assist fashion design with fabric features influenced by historical and cultural development.

New Clavelina (Ascidiacea) Species from the Bahamas

The ascidian fauna of the Bahamas remains grossly understudied. Here, we examined specimens of the genus Clavelina collected from four Bahamian islands using morphological observations and genetic barcoding. Only three species of Clavelina have been previously reported in the Caribbean: C. picta, C. oblonga, and C. puertosecensis. Here, we report C. picta and three species new to science: C. rochae, C. pawliki, and C. erwinorum. C. picta and C. pawliki were found in the northernmost island surveyed, while C. rochae and C. erwinorum were particularly prevalent on the southeastern Bahamian islands. A complete review of genetic barcoding data and morphological characters of accepted Clavelina species was performed. The unique combination of in vivo coloration, morphological characteristics, haplotypes, and species distribution supported the establishment of three new species, significantly adding to the diversity of the genus Clavelina in the Caribbean.

Effects of visual diet on colour discrimination and preference.

To what extent is perception shaped by low-level statistical regularities of our visual environments and on what time scales? We characterized the chromatic 'visual diets' of people living in remote rainforest and urban environments, using calibrated head-mounted cameras worn by participants as they went about their daily lives. All environments had chromatic distributions with the most variance along a blue-yellow axis, but the extent of this bias differed across locations. If colour perception is calibrated to the visual environments in which participants are immersed, variation in the extent of the bias in scene statistics should have a corresponding impact on perceptual judgements. To test this, we measured colour discrimination and preferences for distributions of colour for people living in different environments. Group differences in the extent of blue-yellow bias in colour discrimination were consistent with perceptual learning in local environments. Preferences for colour distributions aligned with scene statistics, but not specifically to local environments, and one group preferred distributions along an unnatural colour axis orthogonal to that dominant in natural scenes. Our study shows the benefits of conducting psychophysics with people at remote locations for understanding the commonalities and diversity in human perception.

Single cell, Label free Characterisation of Human Mesenchymal Stromal cell Stemness and Future Growth Potential by Autofluorescence Multispectral Imaging.

To use autofluorescence multispectral imaging (AFMI) to develop a non-invasive assay for the in-depth characterisation of human bone marrow derived mesenchymal stromal cells (hBM-MSCs). hBM-MSCs were imaged by AFMI on gridded dishes, stained for endpoints of interest (STRO-1 positivity, alkaline phosphatase, beta galactosidase, DNA content) then relocated and results correlated. Intensity, texture and morphological features were used to characterise the colour distribution of regions of interest, and canonical discriminant analysis was used to separate groups. Additionally, hBM-MSC lines were cultured to arrest, with AFMI images taken after each passage to investigate whether an assay could be developed for growth potential. STRO-1 positivity could be predicted with a receiver operator characteristic area under the curve (AUC) of 0.67. For spontaneous differentiation this was 0.66, for entry to the cell-cycle it was 0.77 and for senescence it was 0.77. Growth potential (population doublings remaining) was estimated with an RMSPE = 2.296. The Mean Absolute Error of the final prediction model indicated that growth potential could be predicted with an error of ± 1.86 doublings remaining. This non-invasive methodology enabled the in-depth characterisation of hBM-MSCs from a single assay. This approach is advantageous for clinical applications as well as research and stands out for the characterisation of both present status as well as future behaviour. The use of data from five MSC lines with heterogenous AFMI profiles supports potential generalisability.

Exploring and Practicing the Quantification of Interior Design Colors from an IKEA Design Perspective

With the improvement of life quality, color plays an increasingly important role in interior design. This article, guided by IKEA's design philosophy, deeply explores the scientific method of interior design color quantification, aiming to enhance the aesthetics and functionality of the living environment through precise color matching. The method leverages the dkimageapp module to achieve scientific quantification and analysis of colors, thereby accomplishing efficient color pairing. In terms of methodology, this article elaborates on the importance and application of color palette, color difference, and color wheel calculations. Color palette calculation assists designers in grasping the distribution and harmony of colors; color difference calculation utilizes the CIEDE2000 formula to provide an accurate assessment of color differences; color wheel calculation serves as a visual tool for understanding color relationships. Empirical research has verified the effectiveness and practicality of the algorithms, ensuring the reliability of the study. This article ultimately summarizes the research findings and looks forward to their widespread application in the field of interior design, contributing to the creation of a better living environment, while stimulating further exploration and innovation to promote the continuous development of the interior design industry

T and Z, partial seed coat patterning genes in common bean, provide insight into the structure and protein interactions of a plant MBW complex.

Flavonoids are secondary metabolites associated with plant seed coat and flower color. These compounds provide health benefits to humans as anti-inflammatory and antioxidant compounds. The expression of the late biosynthetic genes in the flavonoid pathway is controlled by a ternary MBW protein complex consisting of interfacing MYB, beta-helix-loop-helix (bHLH), and WD40 Repeat (WDR) proteins. P, the master regulator gene of the flavonoid expression in common bean (Phaseolus vulgaris L.), was recently determined to encode a bHLH protein. The T and Z genes control the distribution of color in bean seeds and flowers and have historically been considered regulators of the flavonoid gene expression. T and Z candidates were identified using reverse genetics based on genetic mapping, phylogenetic analysis, and mutant analysis. Domain and AlphaFold2 structure analyses determined that T encodes a seven-bladed β-propeller WDR protein, while Z encodes a R2R3 MYB protein. Deletions and SNPs in T and Z mutants, respectively, altered the 3D structure of these proteins. Modeling of the Z MYB/P bHLH/T WDR MBW complex identified interfacing sequence domains and motifs in all three genes that are conserved in dicots. One Z MYB motif is a possible beta-molecular recognition feature (β-MoRF) that only appears in a structured state when Z MYB is modeled as a component of a MBW complex. Complexes containing mutant T and Z proteins changed the interaction of members of the complex in ways that would alter their role in regulating the expression of genes in the flavonoid pathway.