Perceived Color Differences Research Articles

Emotional Context and Color Perception and Recognition by 12- and 16-years-old Children

Will the emotional context in which a painting is placed impact how well adolescents remember the colors in it? Will there be differences in color perception and recognition based on age and gender? Specific materials had to be designed to answer this question: (a) an abstract, themeless painting composed of twelve colors, each covering the same area with the same number of pixels, and (b) four texts with different emotional connotations (fear, anger, happiness, and sadness) describing the lives of fictitious painters. After being pretested, the material was proposed to 142 seventh-grade students and 71 tenth-grade students. Each subject studied a painting and heard one of the four texts. Next, the painting was taken away; after this, the subjects ordered the twelve colors based on how much area they thought each one covered the painting. It was hypothesized that the subjects would give greater importance to specific colors depending on the emotional context induced by the associated text. The results confirmed this hypothesis, although the tenth graders were less affected by the emotional context than the seventh graders. There was no statistically significant effect of gender in either population.

A Method for Evaluating Human Observer's Perception of Color Differences

A Method for Evaluating Human Observer's Perception of Color Differences

Individual Differences in Colour Perception: The Role of Low-Saturated and Complementary Colours in Ambiguous Images.

Individual differences in colour perception, as evidenced by the popular debate of “The Dress” picture, have garnered additional interest with the popularisation of additional, similar photographs. We investigated which colorimetric characteristics were responsible for individual differences in colour perception. All objects of the controversial photographs are composed of two representative colours, which are low in saturation and are either complementary to each other or reminiscent of complementary colours. Due to these colorimetric characteristics, we suggest that one of the two complementary pixel clusters should be estimated as the illuminant hue depending on assumed brightness. Thus, people perceive the object's colours as being biased toward complementarily different colour directions and perceive different pixel clusters as chromatic and achromatic. Even though the distance between colours that people perceive differently is small in colour space, people perceive the object's colour as differently categorized colours in these ambiguous photographs, thereby causing debate. We suggest that people perceive the object's colours using different “modes of colour appearance” between surface-colour and self-luminous modes.

Color-difference evaluation for 3D objects.

A psychophysical experiment using 3D printed samples was conducted to investigate the change of perceived color differences caused by two different illuminations and two 3D sample shapes. 150 pairs of 3D printed samples around five CIE color centers [Color Res. Appl. 20, 399-403, 1995], consisting of 75 pairs of spherical samples and 75 pairs of flat samples, with a wide range of color differences covering from small to large magnitude, were printed by an Mcor Iris paper-based 3D color printer. Each pair was assessed twice by a panel of 10 observers using a gray-scale psychophysical method in a spectral tunable LED viewing cabinet with two types of light sources: diffuse lighting with and without an additional overhead spotlight. The experimental results confirmed that the lighting conditions had more effect on the perceived color difference between complex 3D shapes than between 2D objects. The results for 3D and 2D objects were more similar under only diffuse lighting. Current 3D results had good correlations with previous ones [Color Res. Appl. 24, 356-368, 1999; J. Opt. Soc. Am. A 36, 789-799, 2019] using 2D samples with large color differences, meaning that color-difference magnitude had more effect on perceived color differences than sample shape and lighting. Considering ten modern color-difference formulas, the best predictions of the current experimental data were found for CAM02-LCD formula [Color Res. Appl. 31, 320-330, 2006]. For current results, it was also found that predictions of current color-difference formulas were below average inter-observer variability, and remarkable improvements were found by adding power corrections [Opt. Express 23, 597-610, 2015].

Influence of viewing distance on visual color differentiation in vitro.

To investigate whether viewing distance influences the results of visual tooth color differentiation. A total of 65 students underwent both theoretical and practical training by a standardized lecture on the use of an internet learning module (Toothguide Trainer, VITA Zahnfabrik) and a standardized training program (Toothguide Training Box) for visual shade-taking. Each student matched 10 randomly selected shade tabs presented at different viewing distances (arm's length distance [AL, 70 cm] and AL/2 [35cm]) under lateral, non-glare lighting at a 45-degree angle with a color differentiation lamp. The results were recorded as to what extent the presented and selected tabs of the color determination matched. The overall median values of perceived color difference (ΔE) were 1.6 for AL/2 and 3.2 for AL, and these values were significantly different (P < .001). Within the limitations of this study, it was shown that the viewing distance had a significant influence on the color deviation in tooth color assessment. Therefore, a smaller viewing distance of 35 cm for shade determination is recommended.

Influence of background color on color perception in dentistry

ObjectiveTo evaluate the influence of neutral color backgrounds on the perception of color differences in dentistry. MethodsA software was developed for this study that calculated the perceptibility (PT) and acceptability (AT) thresholds of color differences between a pair of computer-simulated incisor samples (n = 60 pairs) over three neutral color (white, gray and black) backgrounds. CIELAB and CIEDE2000 color difference formulas were used. Five groups of volunteer observers (N = 100) participated in the psychophysical experiment (n = 20): Dentists; Dental students; Dental auxiliaries; Dental technicians; and Laypersons. The psychophysical experiment was performed in a dark environment on a calibrated high-resolution screen. To determine PT and AT values, the 60 pairs of samples were randomly presented to each observer over the different backgrounds. The data were adjusted (TSK Fuzzy) and analyzed statistically using Student t-test and ANOVA (α = 0.05). ResultsRegardless of the metric and the background used, the PT values showed no difference among different observers (p > 0.05). Dentists showed the lowest PT values. Dental technicians showed the lowest AT (p ≤ 0.05) and similar values for the three backgrounds (p > 0.05), regardless of the metric used. The other groups of observers showed the lowest and the highest AT values when using black and white backgrounds, respectively (p ≤ 0.05). ConclusionsThe lowest AT values using a black background indicates that the use of this background allows for the evaluation of slight color differences, and should be used for challenging color differences in esthetic dentistry. This study showed the influence of the observer experience on color evaluation in dentistry. Clinical significanceThere was no influence of the background color on the perceptibility threshold. However, dentists and dental technicians showed greater ability to perceive slight color differences compared to other groups of observers.

Perceptually uniform cross-gamut mapping between surface colors.

Gamut mapping is an important part of the color reproduction pipeline. A color's appearance depends on the gamut achievable by the reproduction device (e.g., display, printer, etc.) or the reproduction material (e.g., plastics, paints, textiles, etc.). In the surface color industry, often a single color is managed such that, if it lies outside of the reproduction gamut, it would be mapped to a visually similar color on the boundary of the reproduction gamut using a gamut mapping algorithm. The algorithm's performance mainly depends on the uniformity of the working color space and/or selection of a focal point, inside the reproduction gamut, towards which the mapping line should be directed. Hitherto, the CIE standard color difference formula CIEDE2000 is the best known perceptual color difference metric for the standard dynamic range. In this paper, a method is proposed with the aim to achieve perceptually uniform mapping of a source color to the reproduction gamut using the CIEDE2000 as reference for uniformity. The proposed method, named UNIMAP00, is independent of the uniformity of the working color space, and no focal points are needed. The current results closely agreed with the experimental findings previously reported by other researchers.

Characterization of Color Differences for Color Palettes

Various color difference metrics were developed for characterizing the perceived color difference between individual color patches. Color difference between palettes containing multiple color patches, however, is critically important in product design and computer graphics. This study aimed to investigate how the perceived color difference between a pair of color palettes containing more than a single color patch is affected by the order and number of color patches in the palette. Two reference color sets were generated and each set had four color palettes containing 1, 4, 9, and 16 color patches that were arranged as 1 × 1, 2 × 2, 3 × 3, and 4 × 4 patterns. Human observers scaled the color differences between a color palette of the reference set and a color palette that had revised colors, or revised orders, or a combination of revised colors and orders compared to the reference palette. The calculated color differences between the two palettes were derived using the Minimum Color Difference Model (MICDM) algorithm proposed in a recent work with different color difference metrics, including CIELAB, CMC, CIE94, and DE2000. It was found that the perceived color differences of pairs of individual color patches were significantly larger than those containing multiple patches, when the calculated color differences were the same. The color differences metrics, except for CIE94, had similar performance when characterizing perceived color differences between color palettes.

ΔEITP is Now Ratified as ITU-R BT.2124—Is the Industry Ready to Move on from ΔE2000?

For many years, $\Delta E 2000$ has been considered the industry standard for estimating perceptual color differences and evaluating the color accuracy of display technologies. Recently, the International Telecommunication Union (ITU) released Recommendation ITU-R BT.2124, which defines a new metric, $\Delta E_{\mathrm {ITP}}$ , as the new standard for evaluating perceptual color differences. Given this new recommendation, it is important that we become familiar with how $\Delta E_{\mathrm {ITP}}$ performs in practice and what can be expected when using it in existing workflows. A key part in this process is having an understanding of the properties of the color space that the color difference metric is based on and how that relates to the intended application of the metric. In this paper, we explore this relationship as it pertains to the $\Delta E2000$ and $\Delta E_{\mathrm {ITP}}$ color difference metrics, specifically in the context of evaluating color reproduction on self-luminous displays. Simulated data and measured data from calibrated displays are used to compare the performance of the metrics. Given that $\Delta E 2000$ and $\Delta E_{\mathrm {ITP}}$ are based on significantly different derivation principles, there are notable differences that must be acknowledged between these two metrics, especially as we transition between them. It is highly likely that $\Delta E 2000$ has been underpredicting perceptual color differences, significantly so when used for the evaluation of high dynamic range (HDR) and wide color gamut (WCG) displays.

A new blind color watermarking based on a psychovisual model

In this paper, we address the problem of the use of a human visual system (HVS) model to improve watermark invisibility. We propose a new color watermarking algorithm based on the minimization of the perception of color differences. This algorithm is based on a psychovisual model of the dynamics of cone photoreceptors. We used this model to determine the discrimination power of the human for a particular color and thus the best strategy to modify color pixels. Results were obtained on a color version of the lattice quantization index modulation (LQIM) method and showed improvements on psychovisual invisibility and robustness against several image distortions.

Analysis of color differences in stained contemporary esthetic dental materials

Statement of problemAlthough contemporary analytical methods are available for application to data which exhibit a lack of equality of variances or a lack of normality in the error distribution, little guidance is provided for selecting the methods of data handling and analysis which best fit color difference data for stained esthetic materials. PurposeThe purposes of this in vitro study were to apply information criteria of analysis of variance (ANOVA) methods of differing error distributions and covariance structures when analyzing color differences to determine the degree of alienation among 3 Commission Internationale de l’Eclairage (CIE) color difference formulae to assess the linearity of relationships among these formulae and to independently assess differences among various computer-aided design and computer-aided manufacture (CAD-CAM) materials in any color change after common forms of staining over time. Material and methodsHybrid ceramic, resin nanoceramic, feldspathic-ceramic, and lithium-disilicate ceramic specimens (N=128) were subjected to staining from water, tea, coffee, and red wine over 1, 7, and 30 days, with color differences calculated from baseline. Akaike information criteria (AIC) and Bayesian information criteria (BIC) values were determined for Gaussian and lognormal error distributions at covariance structures of standard variance components and compound-symmetry. The analysis of variance used to analyze any significant effects on these color differences was the one with the lowest AIC and BIC values. Then, for each solution, day, and CIE color difference formula, any significant difference in the color differences between all pairs of materials was found by Bonferroni-corrected Student t tests. Those statistically significant pairwise comparisons where the larger of the color differences met or exceeded the acceptability threshold were labeled as statistically and visually noteworthy. ResultsFor this color difference data set, the lognormal error distribution and the covariance structure of compound symmetry provided the best AIC and BIC. Because the interaction between material, solution, and day was statistically significant (P<.001), pairwise comparisons were made between all pairs of materials for each level of solution and day studied. Noteworthy differences were identified, where hybrid ceramic and resin nanoceramic each had color changes after staining in coffee and red wine that were greater than each of feldspathic-ceramic and lithium-disilicate ceramic. ConclusionsAIC and BIC values evaluate distinctively the Gaussian and lognormal error distributions when analyzing highly varying color differences. Although there is a high linear correlation between the 3 color difference formulae studied, each formula is unique, and each represents a different assessment of the perceived color difference. CAD-CAM materials, staining liquids, and time points affected the notable color changes.

Специфика перевода колористической лексики в произведениях О. Уайльда на русский язык

The study aims to identify translation methods and describe peculiarities of using transformations in translating colouristic vocabulary into Russian. The research is novel in that it is the first to determine specifics of translating colour terms using O. Wilde’s short stories and tales. As a result of the study, it is possible to conclude that the Russian texts mostly feature equivalent translations of colour terms. Nevertheless, differences in colour perception and language structures cause certain difficulties in translating colouristic vocabulary, which leads to using various transformations in order to achieve adequate translation (substitution, transposition, omission, addition).

Image Quality Assessment by Combining Masking Texture and Perceptual Color Difference Model

Objective image quality assessment (IQA) models have been developed by effective features to imitate the characteristics of human visual system (HVS). Actually, HVS is extremely sensitive to color degradation and complex texture changes. In this paper, we firstly reveal that many existing full reference image quality assessment (FR-IQA) methods can hardly measure the image quality with contrast and masking texture changes. To solve this problem, considering texture masking effect, we proposed a novel FR-IQA method, called Texture and Color Quality Index (TCQI). The proposed method considers both in the masking effect texture and color visual perceptual threshold, which adopts three kinds of features to reflect masking texture, color difference and structural information. Furthermore, random forest (RF) is used to address the drawbacks of existing pooling technologies. Compared with other traditional learning-based tools (support vector regression and neural network), RF can achieve the better prediction performance. Experiments conducted on five large-scale databases demonstrate that our approach is highly consistent with subjective perception, outperforms twelve the state-of-the-art IQA models in terms of prediction accuracy and keeps a moderate computational complexity. The cross database validation also validates our approach achieves the ability to maintain high robustness.

Determining Tolerance Values of Instrumentally Measured Color Differences to Evaluate Black Filament Yarns

There are many factors affecting the tolerance values of instrumentally measured color differences, including variety of industries, type of products to be matched with the original samples, the need of customers, etc. Regarding the insufficiency of various color difference formulae to deal with the acceptability of color matching of reproduced samples with the target, some researchers tried to present an instrumental color tolerance limit in accordance with the results of visual assessment experiments. Considering the specific colorimetric attributes of achromatic samples (with low lightness and chroma values), it was tried to set an instrumental tolerance limit based on the measured and visually perceived color differences between 20 filament black yarns and the reference one. The results showed that determining the color tolerance value based on various color difference formulae, i.e. ΔEa*b*, CIE94, CIE2000 and CMC (2:1), results in different instrumental wrong decisions, while the ΔE*ab color difference equation with the color tolerance value of 0.5 for filament black yarns showed the minimum number of wrong decisions.

Observer metamerism to display white point using different primary sets.

Displays with different primary sets were found to introduce perceived color mismatch between stimuli that are computationally metameric and to affect the variations of the perceived color difference of metameric stimuli among observers (i.e., observer metamerism). In this study, computational analyses and psychophysical experiments were carried out to investigate the possibilities of increasing the color gamut area of a commercially available liquid crystal display (LCD) system using 16 three-primary sets, so that the perceived color difference of the white point between the system and the reference display and observer metamerism can be minimized. It was found the primary set with the peak wavelengths of 450, 525, and 665 nm was able to increase the sRGB color gamut by 72.1% in the CIE 1931 chromaticity diagram, which was found to have a strong correlation to the color volume of wide color gamut displays, while introducing the minimal color mismatch to the white point of the reference display and observer metamerism. The small white point color mismatch could be due to the similar wavelengths of the blue and green primaries in comparison to the reference display. In addition, the experiment results suggested that the CIE 2006 2° Color Matching Functions (CMFs) had better performance in characterizing the color match of the white point than the CIE 1931 2°, 1964 10°, and 2006 10° CMFs, which could be due to the fact that the stimulus used in the experiment only had a field of view (FOV) around 3.8°.

Visual Color Difference between Colored-Yarn Mixed Woven Fabrics and Their Instrumentally Measured Colors: the Effects of Individual Yarn Colors and Texture

The study investigated the differences between perceived and instrumentally measured colors of woven fabrics in which different colored yarns are woven together such that they are perceived as solid colors. Cyan, magenta, and yellow yarns were woven together to produce 63 fabrics in a wide range of colors, the values of which were measured spectrophotometrically. The measured colors were generated as solid color images on a calibrated cathode ray tube (CRT) monitor. Then the fabrics were scanned and their scanned images were displayed beside their corresponding solid color images on the CRT monitor to evaluate the visual color difference between them. The results showed that the individual yarn colors and their interlacement on the fabric surface influenced the overall color appearance. Although the woven and solid colors in each pair had identical CIELAB color values, the perceived color difference was as large as 5.68 ΔE*ab,10 on average. Fabrics composed of various colors of yarn were found to have larger visual color differences from their measured colors than those composed of single colors of yarn. The visual color difference varied according to texture, but texture strength, which has been widely reported as a strong parametric factor in visual color difference evaluation, was not shown to have had a consistent effect. This study also examined how the overall color attributes, including the lightness, chroma, and hue, of fabrics affected the visual color difference and developed a predictive model of those effects.

How to make a #theDress.

If we completely understand how a phenomenon works, we should be able to produce it ourselves. However, the individual differences in color appearance observed with #theDress seem to be a peculiarity of that photo, and it remains unclear how the proposed mechanisms underlying #theDress can be generalized to other images. Here, we developed a simple algorithm that transforms any image with bicolored objects into an image with the properties of #theDress. We measured the colors perceived in such images and compared them to those perceived in #theDress. Color adjustments confirmed that observers strongly differ in how they perceive the colors of the new images in a similar way as for #theDress. Most importantly, these differences were not unsystematic, but correlated with how observers perceive #theDress. These results imply that the color distribution is sufficient to produce the striking individual differences in color perception originally observed with #theDress-at least as long as the image appears realistic and hence compels the viewer to make assumptions about illuminations and surfaces. The algorithm can be used for stimulus production beyond this study.

What Color Does the Consumer See? Perceived Color Differences in Plastic Products in an LED-Lit Environment

To attract customers and increase market opportunities, retailers frequently use lighting to highlight the color of their products. However, differences between perceived and actual color, triggered by display lighting, can motivate buyers to discard products after purchase. Few studies have been reported on differences in perceived color, caused by LEDs. This study focuses on two correlated color temperatures (2800 K, 4000 K) and illuminance levels (500 lx, 1500 lx) to create four LED-lit environments, and measures the differences in the color perceived by 20 observers on acrylonitrile–butadiene–styrene (ABS) plastics, with different surfaces, under these four environments. The results reveal that correlated color temperature results in larger perceived differences in color than illuminance, and the effects of LED light sources on green and yellow ABS plastic products are more obvious than their effects on red and blue products. One possible reason for this can be attributed to the visual sensitivity effect of human eyes. The results of this study can serve as a reference for designers fabricating ABS plastic products for practical lighting applications, and improving the role of LED lighting in sustainable development.

Replication of Screen-Printing Fabric via Ink-jet Textile Printing

Digital textile printing (DTP) is fast, flexible, and relatively inexpensive for sample printing, and can be applied quickly in response to consumer demand. The aim of this two-stage research was to analyze the potential of DTP to replace traditional screen printing for a specific textile product. In Stage One, an optimal DTP workflow was established. The workflow included determination of the colorant and substrate combination, color calibration, CAD file, and the necessity of pretreatment. In Stage Two, a visual assessment instrument and protocol were established to evaluate the acceptance of replicated ink-jet printed fabric. The visual assessment and protocol were designed to evaluate the acceptance of the ink-jet printed sample to fully replicate the screen-printed sample via seven measured aspects. These seven aspects include: perceived color difference, lightness difference, overall color, scale, line quality, visual texture, and overall appearance. Data gathered from the visual assessment was then analyzed and compared using SPSS statistics software. The results indicate that DTP demonstrates a significant potential alternative for traditional screen printing.

Культурологические аспекты в обучении китайскому языку как иностранному

The paper discusses the problems of intercultural learning when teaching Russian students Chinese as a foreign language. The relationship between language and culture is revealed, and the terms ‘intercultural dialogue’, ‘cultural barrier’, and ‘national mentality’ are considered. The concepts of culture, communication, and intercultural communication are defined as well. The author emphasizes the importance of studying the culture of the Chinese people while teaching Chinese as a foreign language. The research illustrates the influence of culture on human reaction in case of external objective irritation. The study shows the differences in semantic associations of color and taste perception by the bearers of Chinese and Russian cultures. The paper reveals the causes of differences in color perception and the use of basic colors in different cultures. The author concludes that cultural and intercultural aspects play an important role in learning a foreign language. At the same time, the intercultural approach becomes a basic teaching approach.