Background Color Research Articles

This study examined the reliability of adiposity (%Fat) measured from a single digital image using a smartphone-based application with different color backgrounds. A reference image was obtained while participants (n = 32) stood in front of a white background (WB), with additional images obtained in front of black, green, orange, and gray backgrounds. A contrast ratio was calculated between the background and clothing RGB hexadecimal color values. Linear mixed-effects modeling determined if color contrasts explained the background effect on %Fat estimation. The Green, Orange, and Gray conditions yielded constant error (CE) roughly 1.0 %Fat, with greater CE observed in the Black background. Neither the within person-contrast (p = 0.638) nor the between-person contrast (p = 0.451) was associated with the CE and did not explain any extra variability in the CE (χ2 = 0.83, p = 0.660). Images with darker background colors may result in greater CE due to lower contrast between the background and clothing.

Host-parasite arms races facilitate rapid evolution and can fuel speciation. Cuculus cuckoos are deceptive egg mimics that exhibit a broad diversity of counterfeit egg phenotypes, representing host-adapted subpopulations (gentes). Genome analysis of 298 common (Cuculus canorus) and 50 oriental cuckoos (Cuculus optatus) spanning 15 egg morphs revealed that eggshell background coloration is predominantly influenced by matrilineal genetic variation. Recurrent mitochondrial mutations and an ancient W chromosome-linked translocation of an autosomal assembly factor for respiratory complex I provide a tentative link between mitochondrial function and pigment synthesis through the heme pathway. Biparentally inherited loci contribute to phenotypic variation in both species, mainly for maculation. The evolutionary tug-of-war over a sex-limited, mimetic trait integrates autosomal components with the nonrecombining, matrilineal genome without catalyzing genome-wide divergence between gentes.

Abstract Flower color is an essential biological and ornamental trait in plants. Paeonia rockii (Flare tree peony, FTP) exhibits diverse flower colors, characterized by a distinctive basal flare in petals, which enhances its ornamental and ecological value. However, while previous research has mainly focused on flare formation, the regulatory mechanisms controlling the background color of petals remain unclear. This study identifies a novel regulatory module governing petal background coloration in FTP. Within this module, PrMYB75a acts as the central regulator to promote anthocyanin accumulation, as evidenced by stable transformation in Arabidopsis thaliana and tobacco (Nicotiana tabacum), as well as virus-induced gene silencing in FTP. Furthermore, yeast one-hybrid, dual-luciferase reporter, and electrophoretic mobility shift assays collectively demonstrated that PrMYB75a directly activates two key anthocyanin structural genes, PrCHS1 and PrANS, by interacting with MYB-binding sites nearest to the ATG start codon in their promoters. Additionally, we identified an upstream regulator, PrFRS2, which activates both PrMYB75a and PrANS by binding to the FAR1/FHY3-binding sites in their promoters. Modulation of PrFRS2 expression levels through gene silencing and overexpression resulted in alterations in flower pigmentation in both FTP and tobacco. In summary, within the PrFRS2-PrMYB75a module, PrFRS2 indirectly activates PrCHS1 and PrANS by regulating PrMYB75a, or directly activates PrANS, leading to anthocyanin accumulation in FTP purple petals. This module represents a novel regulatory mechanism of petal background coloration in FTP, providing new perspectives on color variation in flowering plants and offering genetic resources for the improvement of the flower color trait in tree peonies.

The subject of the article is the development of an inexpensive optical system based on an RGB sensor for de-tecting camouflaged objects in a military environment. The aim of the research is to create a prototype hardware and software system for detecting camouflage based on an RGB sensor operating in the visible light spectrum, with subsequent experimental verification of its effectiveness in various natural conditions. The system is characterized by low power consumption, mobility, and can be integrated into portable or un-manned reconnaissance platforms. To achieve the set goal, the following tasks were solved: development of the hardware structure of the sensor system based on available components; implementation of algorithms for background modeling, color anomaly detection, and noise filtering using colorimetric analysis in RGB space; conducting a series of field experiments in various natural conditions – wooded areas, steppe zones, and rocky landscapes; evaluating the accuracy, stability, and limitations of the proposed solution in comparison with thermal imagers and infrared cameras with artificial intelligence. The methodology is based on the use of a TCS34725 RGB sensor with a built-in infrared filter and a 16-bit ADC in combination with an ESP32 microcontroller, which provides real-time data processing, wireless data transmission, and autonomous operation. The detection algorithm is based on the formation of a color background profile, analysis of deviations by Euclidean distance, normalization of RGB values, median filtering, and adaptive threshold determination, which ensures resistance to environmental changes. Test results showed that the proposed system is capable of accurately identifying digital «pixel» camouflage in wooded areas (86 %), multicam camouflage in steppe conditions (78 %), and plain olive camouflage on rocky backgrounds (65 %). A comparison with thermal imaging and IR systems confirmed the significant advantages of the RGB solution in terms of cost (less than $ 20), energy efficiency, and mobility, although it can only operate during daylight hours. The conclusions emphasize the feasibility of using RGB detection systems as a cost-effective auxiliary tool for reconnaissance and security tasks. The scientific novelty of the work lies in the integration of a simple and affordable RGB sensor with adaptive algorithms for background modeling and color deviation analysis, which allows the creation of low power platforms for camouflage detection. Unlike traditional approaches, the proposed system opens up prospects for deploying a distributed network of inexpensive sensor nodes or integrating them into unmanned aerial vehicles for operational monitoring of large areas.

This study analyzes the visual and typographic elements used in Turkish cologne packaging, examining how brands visually represent different scents. Through a content analysis of design components such as background style, color, imagery, typography, and graphical structures, the study aims to identify current trends in scent representation within packaging design. A dataset of 83 cologne products from 17 brands is systematically categorized to map out contemporary approaches to scent-based visual representation. Findings indicate a predominant reliance on solid backgrounds (50.6%), illustrative imagery (81.1%), and geometric shapes (78.6%), with sans-serif typography (52.2%) being the most common choice for scent names. Brands demonstrate two primary visualization strategies: aligning their designs with the scent itself or maintaining a consistent corporate identity across various fragrances. By mapping how scents are visually expressed in Turkish cologne packaging, this study provides insights into the role of visual representation in fragrance perception and contributes to the understanding of contemporary design practices in scent-based product packaging.

BackgroundFacultative, physiological color change has many potential adaptive functions, and the ability of the green anole (Anolis carolinensis) to shift between brown and green coloration is no exception. Three non-mutually exclusive hypotheses for such color changes include: 1) The camouflage hypothesis, which states that individual anoles use brown and green coloration to blend into their background; 2) The social signaling hypothesis, which states that coloration shifts convey intraspecific signals such as dominance, submission, and mating status during interactions; 3) The thermoregulation hypothesis, which states that shifting to darker brown coloration during colder temperatures allows for increased absorption of solar radiation as heat.ResultsWe showcase the utility of a computer vision pipeline to derive individual-level color (green versus brown) from a large dataset of citizen science observations spanning the southeastern USA. We used this color information along with climate, seasonal timing information and background in images to test associations between color morph, temperature and time of year. Results show that brown-presenting A. carolinensis were observed more frequently at lower temperatures during winter. However, the observed correlation between presenting color and temperature was absent during the summer breeding season. We did not find strong evidence for background color matching.ConclusionWe found support for both the thermoregulatory hypothesis and social signaling hypothesis dependent on time of year, which suggests multiple independent drivers are influencing physiological color changes in A. carolinensis. Further, this work shows the power of leveraging large-scale digital field images and machine learning to derive insights about how species can regulate phenotype to maintain their thermal and biotic niche optima.

Capillary malformations (CMs) are congenital malformations of capillaries typically visible as blanchable, pink to brown patches on the skin and/or mucosa. The genetic cause of CMs guides diagnosis, treatment, and recurrence counseling. However, identification may be limited by the availability of samples, the type of tests, and insurance coverage. We hypothesize that there are distinct dermoscopic features associated with specific genotypes of congenital CMs. A single-center, retrospective cohort study of 22 patients with CMs affecting the skin, a polarized dermoscopic photo of the lesion, and a single nucleotide variant in the EPHB4, GNA11/GNAQ, PIK3CA/PIK3R1, or RASA1 genes was performed. Three reviewers analyzed dermoscopic photos for the presence of apparent vessels, branching, lacunae, geometric shape formation, zones of dropout, follicle-sparing, vessel and background color, and length and width of vessels when discernable. Features were categorized by genotype. EPHB4-CMs have visible lengthwise and widthwise cross sections of vessels that exhibit branching. RASA1-CMs generally present with merely a red/pink/brown hue without visible vessels. GNA11 or GNAQ-CMs generally present with pink coloration and generally only with visible widthwise cross sections of vessels without branching. Geometric PIK3CA-CMs exhibit distinct purple lacunae that indicate a lymphatic component, but the reticulated PIK3CA-CMs otherwise demonstrate a varied presentation. Our research identified distinct genotype-phenotype correlations for CMs by dermoscopy. Dermoscopy can narrow the differential diagnosis, guide genetic testing, and aid in the interpretation of variants of uncertain significance (VUS). This study demonstrates that dermoscopy holds promise in aiding genetic diagnosis and ultimately medical management.

Influence of tank geometry and background color on growth performance and immune response of endangered Indian butter catfish Ompok bimaculatus

ABSTRACT Cultural product design seeks to embody the essence of a culture by merging traditional aesthetics with modern functionality, thereby preserving and advancing cultural identity through innovative methodologies. This research proposes a creative framework for Personalized Pattern Automatic Generation (PPAG) to support cultural pottery design. We adopt a Condition-based Deep Convolutional Generative Adversarial Network (CB-DC-GAN) to rapidly generate culturally inspired pottery patterns with distinctive artistic qualities. A dataset of cultural motifs, comprising various shapes and designs, was collected and standardized through preprocessing techniques such as background color unification, image dimension alignment, and normalization. The CB-DC-GAN produces background and pottery pattern images, which are subsequently refined using color correction and mean filtering to ensure seamless integration. Model evaluation emphasizes color fidelity, edge coherence, and pattern uniqueness as measures of cultural distinctiveness. The proposed approach is implemented in Python and assessed through extensive experimentation. Comparative analysis with traditional pattern-generation methods demonstrates that the model not only enhances the efficiency of cultural pottery design but also achieves superior visual and artistic outcomes. These findings highlight the potential of the PPAG framework to contribute to the preservation and innovation of cultural identity through advanced computational design techniques.

Stimulus repetition is abundant, because the environment is redundant and/or because it is redundantly sampled. This offers an opportunity to optimize the processing of repeated stimuli. Indeed, stimulus repetition leads to classically described neuronal response decreases, and to more recently described neuronal gamma synchronization increases (sometimes preceded by decreases for a few trials). Here, we used a full-screen colored background (FSCB) and a flashed black bar, while recording multi-unit activity (MUA) and local field potentials (LFP) from area V1 of an awake macaque monkey. We found that the FSCB repetition induced neuronal response increases (sometimes preceded by decreases for a few trials) and gamma synchronization decreases (preceded by increases for a few trials). These effects are largely opposite to the dominant previous findings. Intriguingly, these surprising effects reversed when we isolated the responses to the flashed black bar. We discuss these findings, considering differences to previous studies with regards to the subject of the study, the stimuli and the task. We notice that in studies reporting classical results for gamma, sometimes in combination with firing rates, the stimuli were typically (partly) predictive of the reward. Here, we found non-classical results for the FSCB that was not reward predictive, and classical results for the black bar that was reward predictive. Whether this has revealed a general effect of reward predictive versus non-predictive stimuli will require further investigation with stimuli and task designs tailored specifically for this question.

ABSTRACT Menu design includes elements such as patterns, depth and breadth, labelling, and structure, all impacting usability. With the rise of smartphones, many menu patterns have emerged, but icons now play a critical role, indicating that patterns alone don't determine usability. Previous research shows that icon designs, including background colours and symbols, affect menu efficiency and this impact varies across age groups. This study aimed to understand the factors influencing menu selection time, selection errors, and user satisfaction by evaluating menu patterns as another independent variable. We investigated the effects of age groups, menu patterns, icon background colours, and icon symbols on these metrics. A total of 240 participants, divided into children, adults, and older adults (80 per group), took part in the experiment. Results showed that grid menus, multicolour backgrounds, and pictorial symbols significantly improved selection time. Age also significantly affected selection time, with adults being the fastest, followed by children, and then older adults. Based on these findings, we offer design recommendations for smartphone menus and icon designs.

Image-to-image translation inputs an image and transforms it into a new image. Deep learning-based image translation requires numerous training data to prevent overfitting; therefore, this study proposes a method to secure training data efficiently by generating and selecting fake water-droplet images using a cycle-consistent generative adversarial network (CycleGAN) and a convolutional neural network (CNN) for image enhancement under inclement weather conditions. A CNN-based classification model was employed to select 1200 well-formed virtual paired sets, which were then added to the existing dataset to construct an augmented training set. Using this augmented dataset, a CycleGAN-based removal module was trained with a modified L1 loss incorporating a difference map, enabling the model to focus on water-droplet regions while preserving the background color configuration. Additionally, we introduce a second training step with tone-mapped target images based on Retinex theory and CLAHE to enhance image contrast and detail preservation under low-light rainy conditions. Experimental results demonstrate that the proposed framework improves water-droplet removal performance compared to the baseline, achieving higher scores in image quality metrics such as BRISQUE and SSEQ and yielding clearer images with reduced color distortion. These findings indicate that the proposed approach contributes to improving image clarity and the safety of autonomous driving under inclement weather conditions.

Colour prediction for restoring discoloured teeth using zirconia veneers.

Influence of zirconia thickness and background color on color matching accuracy of monolithic zirconia restorations.

A novel multimodal framework for emotion recognition in comics: Integrating background color, facial expressions, and text sentiment using fuzzy logic

ABSTRACT Neurodiverse children do not always benefit from a typical learning environment and therefore may be at a disadvantage when learning alongside their peers. Many of these children have different preferences when it comes to the formatting of learning materials, which may impact their performance. The current study examined the preferences of 204 adults with diagnosed ADHD, autism, dyslexia, dyscalculia, and dyspraxia to identify formatting preferences for formatting variables previously shown to influence performance: font style, font size, character spacing, line spacing, title design, background colour, reward icon and instruction layout. Preferences were obtained by means of a survey, where participants rated their preferences on 5-point, Likert-type scales (1 = strongly disagree to 5 = strongly agree). Participants were also asked to rank the options provided for each formatting variable from least favourite to favourite. Results indicated consistent preference across all neurodiverse groups, with one category in each being significantly preferred across all groups. The exception to this was background colour, in which each neurodiverse group preferred a different colour.

Purpose The monotonous lighting environment in extra-long tunnels often induces mind-wandering in drivers. To address this issue, this study explores effective strategies to optimize tunnel lighting environments by configuring various background colors and special lighting zones to enhance the alertness of young drivers and ensure driving safety. Methods A virtual driving simulator was utilized to carry out the experiment. By integrating heart rate variability (HRV) indicators with facial expression analysis technology, this study systematically investigates the effects of three background lighting colors—red, blue, and yellow (with a luminance range of 30.5–39.6 cd/m2)—under single-zone and two-zone special lighting stimulation conditions. A non-contact “physiology–behavior” coupling evaluation model based on the XGBoost algorithm is developed to enable real-time monitoring of the mind-wandering levels of young drivers (K-values), providing an alternative to traditional electrode-based detection methods. Results Two-zone special lighting stimulation significantly improved driver alertness and arousal compared to single-zone stimulation. Under red background lighting with two-zone stimulation, the LF/HF ratio decreased by 32.6% (p < 0.05), and a continuous decline in neutral facial expression scores indicated a sustained alerting effect. In contrast, blue background lighting demonstrated the best performance under single-zone stimulation, reducing the LF/HF ratio by 8.39% and suggesting a short-term stress-relief advantage. Conclusion This virtual driving simulation study revealed that red and blue background lighting exert distinct effects on mind-wandering regulation. Red light with two-zone stimulation effectively suppressed mind-wandering over time, while blue light with single-zone stimulation provided rapid physiological stress relief. In addition, a heart rate–neutral emotion coupling model was constructed, enabling non-contact mind-wandering assessment through facial expression analysis, thereby simplifying the monitoring process.

ABSTRACT Regarding the ocean background, the painted camouflage on the surface of targets effectively conceals them, providing a strategic defense against military reconnaissance. Accurately predicting the color appearance of both the target and background is crucial for assessing the camouflage’s performance. This study investigates the perceived color attributes (lightness, chroma, and hue) of marine targets against varying ocean backgrounds using memory matching assessments. Visual data reveal that background color slightly influences target hue perception through simultaneous contrast effects, while lightness and chroma remain unaffected. As the image-based color appearance model – iCAM offers a potential solution for extracting color appearance attributes from a complex RGB image, it has been adopted to predict the pixel-wise color appearance of the marine targets. Comparative validation shows iCAM substantially outperforms existing color appearance models in marine environments, establishing its superior capability for naval camouflage assessment and design. Further analysis indicates that chroma predictions are sensitive to changes in the filter kernel size of iCAM and the image size, while lightness and hue predictions remain stable. Notably, undersized kernels systematically underestimate perceived chroma, highlighting the critical importance of parameter optimization.

Abstract Snakes display significant chromatic variability across the Nearctic and Western Palearctic biogeographic regions. Dominant background colours include black, orange, brown, grey, and various shades of olive to grass green. This study evaluated the environmental factors that may determine this variation, focusing on the differences between the Köppen climate types and between venomous and non-venomous species. Photographic images were used to extract colours, which were then decomposed into the Hue-Saturation-Lightness (HSL) scale to generate 14 colour categories (using human-visible colour variation). These categories were used to assess their relationship with environmental conditions and compute functional diversity indices for regional species groups. The analyses indicate that the variability in snake coloration was influenced by climatic-­macrohabitat factors (precipitation, temperature, forest cover), habitat type (semi-aquatic, terrestrial, arboreal, semi-fossorial, fossorial), prey type, foraging behaviour (ambush, active foragers), and reproductive mode (viviparous, oviparous), once phylogenetic relatedness is controlled for. Highly venomous species exhibited higher chromatic overlap compared to non-venomous and mildly venomous species. Desert snakes showed greater chromatic specialization and higher interspecific similarity compared to snakes from other climate types. In contrast, species inhabiting humid hot-temperate climates tended to display more divergent and unique coloration patterns.

Various parameters and observation conditions contribute to the emergence of color. This phenomenon poses a challenge in modern visual communication systems, which are continuously being enhanced through new insights gained from research into specific psychophysical effects. One such effect is the psychophysical phenomenon of simultaneous contrast. Nearly 90 years ago, Kurt Koffka described one of the earliest illusions related to simultaneous contrast. This study examined the perception of gray tone variations in the Koffka ring against different background color combinations (red, blue, green) displayed on a computer screen. The intensity of the effect was measured using lightness difference ΔL00 across light-, medium-, and dark-gray tones. The results were analyzed using descriptive statistics, while statistically significant differences were determined using the Friedman ANOVA and post hoc Wilcox tests. The strongest visual effect was observed the for dark-gray tones of the Koffka ring on blue/green and red/green backgrounds, indicating that perceptual organization and spatial parameters influence the illusion’s magnitude. The findings suggest important implications for digital media design, where understanding these effects can help avoid unintended color tone distortions caused by simultaneous contrast.