Universal models of colour emotion and colour harmony

A new set of quantitative models of colour emotion and colour harmony were developed in this study using psychophysical data collected from 12 regions in the world, including Argentina, China, France, Germany, Hungary, Iran, Japan, Spain, Sweden, Taiwan, Thailand, and the UK. These data have previously been published in journals or conferences (for details see Tables 1 and 2 ). For colour emotion, three new models were derived, showing satisfactory predictive performance in terms of an average correlation coefficient of 0.78 for “warm/cool”, 0.80 for “heavy/light” and 0.81 for “active/passive”. The new colour harmony model also had satisfactory predictive performance, with an average correlation coefficient of 0.72. Principal component analysis shows that the common colour harmony principles, including hue similarity, chroma similarity, lightness difference and high lightness principles, were partly agreed by observers of the same region. The findings suggest that it is feasible to develop universal models of colour emotion and colour harmony, and that the former was found to be relatively more culture‐independent than the latter.     

A study of colour emotion and colour preference. Part II: Colour emotions for two‐colour combinations

Eleven colour‐emotion scales, warm–cool, heavy–light, modern–classical, clean–dirty, active–passive, hard–soft, harmonious–disharmonious, tense–relaxed, fresh–stale, masculine–feminine, and like–dislike, were investigated on 190 colour pairs with British and Chinese observers. Experimental results show that gender difference existed in masculine–feminine, whereas no significant cultural difference was found between British and Chinese observers. Three colour‐emotion factors were identified by the method of factor analysis and were labeled “colour activity,” “colour weight,” and “colour heat.” These factors were found similar to those extracted from the single colour emotions developed in Part I. This indicates a coherent framework of colour emotion factors for single colours and two‐colour combinations. An additivity relationship was found between single‐colour and colour‐combination emotions. This relationship predicts colour emotions for a colour pair by averaging the colour emotions of individual colours that generate the pair. However, it cannot be applied to colour preference prediction. By combining the additivity relationship with a single‐colour emotion model, such as those developed in Part I, a colour‐appearance‐based model was established for colour‐combination emotions. With this model one can predict colour emotions for a colour pair if colour‐appearance attributes of the component colours in that pair are known. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 292–298, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20024     

A study of colour emotion and colour preference. Part III: Colour preference modeling

In this study three colour preference models for single colours were developed. The first model was developed on the basis of the colour emotions, clean–dirty, tense–relaxed, and heavy–light. In this model colour preference was found affected most by the emotional feeling “clean.” The second model was developed on the basis of the three colour‐emotion factors identified in Part I, colour activity, colour weight, and colour heat. By combining this model with the colour‐science‐based formulae of these three factors, which have been developed in Part I, one can predict colour preference of a test colour from its colour‐appearance attributes. The third colour preference model was directly developed from colour‐appearance attributes. In this model colour preference is determined by the colour difference between a test colour and the reference colour (L*, a*, b*) = (50, ?8, 30). The above approaches to modeling single‐colour preference were also adopted in modeling colour preference for colour combinations. The results show that it was difficult to predict colour‐combination preference by colour emotions only. This study also clarifies the relationship between colour preference and colour harmony. The results show that although colour preference is strongly correlated with colour harmony, there are still colours of which the two scales disagree with each other. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 381–389, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20047     

Experimental modeling of colour harmony

This study investigates colour harmony in visual experiments in order to develop a new quantitative colour harmony model. On the basis of new experimental results, colour harmony formulae were developed to predict colour harmony from the CIECAM02 hue, chroma, and lightness correlates of the members of two‐ or three‐colour combinations. In the experiments, observers were presented two‐ and three‐colour combinations displayed on a well‐characterized CRT monitor in a dark room. Colour harmony was estimated visually on an 11 category scale from ?5 (meaning completely disharmonious) to +5 (meaning completely harmonious), including 0 as the neutral colour harmony impression. From these results, mathematical models of colour harmony were developed. The visual results were also compared with classical colour harmony theories. Two supplementary experiments were also carried out: one of them tested the main principles of colour harmony with real Munsell colour chips, and another one compared the visual rating of the new models with existing colour harmony theories. © 2009 Wiley Periodicals, Inc. Col Res Appl, 2010.     

Request for existing experimental datasets on colour emotion and colour harmony

The Technical Committee 1‐86 of the International Commission on Illumination on “Models of colour emotion and harmony” is requesting the submission of datasets for use in developing new models of colour emotion and colour harmony. The data should be submitted to the TC Chair, Dr. Li‐Chen Ou at the National Taiwan University of Science and Technology. © 2012 Wiley Periodicals, Inc. Col Res Appl, 2012     

Psychophysical models of consumer expectations and colour harmony in the context of juice packaging

The aim of this study was to develop psychophysical models that predict the influence of pack colours on consumers' psychological responses of fruit juices, such as visually perceived expectations of freshness, quality, liking, and colour harmony. Two existing colour harmony models derived from experiments involving only uniform colour plaques were tested using the juice packaging experimental data. Both models failed to predict the visual results obtained. Nevertheless, two parameters relevant to chromatic difference and hue difference were somewhat associated with the visual results. This suggested that, among all colour harmony principles for uniform colours, only the equal‐hue and the equal‐chroma principles can be adopted to describe colour harmony of packaging used for juice. This has the implication that the principles of colour harmony may vary according to the context in which the colours are used. A new colour harmony model was developed for juice packaging, and a predictive model of freshness was derived. Both models adopted CIELAB colour attributes of the package colour and the fruit image colour to predict viewers' responses. Expected liking and juice quality can be predicted using the colour harmony model while expected freshness can be predicted using the predictive model of freshness. © 2013 Wiley Periodicals, Inc. Col Res Appl, 40, 157–168, 2015     

Additivity of colour harmony

An additive approach to predict harmony for three‐colour combinations is proposed in this article. It is hypothesised that a three‐colour combination can be seen as a combination of three colour pairs, each generating a harmonious/disharmonious feeling that can be quantified by a two‐colour harmony model the authors previously derived; the average of these three harmony values can then determine the overall harmony. To establish whether this hypothesis was valid, two psychophysical experiments were conducted in the United Kingdom and the United States. Experiment 1 used 6545 three‐colour wheels as the stimuli, presented individually on a calibrated cathode ray tube display. Under the same viewing conditions, Experiment 2 used 111 interior images as the stimuli. In each experiment, 20 British and 31 American participated as the observers. An additional test was undertaken, with 64 observers taking part, to address the issue of large sample size as encountered in Experiment 1, using 90 colour wheels selected randomly from those used in Experiment 1. The experimental results show close agreement between the observers' response and the harmony value predicted by the proposed method, with a correlation coefficient of 0.71 for the 6545 colour wheels, 0.93 for the 111 interior images and 0.88 for the additional 90 colour wheels. The results support the additive approach as a simple but robust method for predicting harmony in any three‐colour combinations, which may also apply to combinations generated by any number of colours. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2011     

Investigation of parametric effects using small colour differences

This experiment was carried out to investigate some viewing parameters affecting perceived colour differences. It was divided into eight phases. Each phase was conducted under a different set of experimental conditions including separations, neutral backgrounds, and psychophysical methods. Seventy‐five wool sample pairs were prepared corresponding to five CIE colour centers. The mean colour difference was three CIELAB units. Each pair was assessed by a panel of 21 observers using both the gray scale and pair comparison psychophysical methods. The assessments were carried out using the three different backgrounds (white, mid‐gray, and black) and a hairline gap between the samples. Assessments on the gray background were repeated using a large (3‐inch) gap between the samples. It was found that the visual results obtained from both psychophysical methods gave very similar results. The parametric effect was small, i.e., the largest effect was only 14% between the white and gray background conditions. These visual data were also used to test four colour‐difference formulae: CIELAB, CMC, BFD, and CIE94. The results showed that three advanced colour‐difference formulae performed much better than CIELAB. There was a good agreement between the current results and those from earlier studies. © 1999 John Wiley & Sons, Inc. Col Res Appl, 24, 331–343, 1999     

Print quality evaluation and applied colour management in coldset offset newspaper print

This article aims to investigate print quality in newspaper print, by considering the appropriate calibration standard and applying colour management. In particular, this article examines the colorimetric properties of eight Norwegian newspaper printing presses, to evaluate the relevant colour separation approach, either by applying custom separation profiles or by using an industry standard profile. The key method underlying the work described here relies on obtaining colour measurements to determine the repeatability of each participant in terms of colour differences. Furthermore, the variation between the eight newspaper printing presses and the variation according to the colorimetric values of the ISO 12647‐3 standard are important parts of the quantitative evaluation. Based on the colour measurements two custom ICC profiles were generated and an industry standard profile “ISOnewspaper26v4.icc” was also used. The first custom profile was generated using averaged colour measurement data set from a test print run, and the second using a data set averaged between measured data and the characterization data set “IFRA26.txt” provided by IFRA. These three profiles were applied to four test images, which were then printed by the eight newspaper printing presses. A psychophysical experiment was carried out to determine the “pleasantness” of the reproductions, which were produced using the three profiles. The results of the study show the performance of the appropriate profile, which is applied to the eight newspaper printing presses to obtain significant best print quality. Eventually the results demonstrate the fact that the print variations in colours between the eight printing presses are larger thanthe difference between the custom and the standard profiles. Hence, the print variations and not the profile selection may have determined the visual print quality. Therefore the study reveals the importance of adopting international standards and methods instead of using insufficiently defined house standards to preserve equal results among different newspaper printing presses. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2011     

A data set for fuzzy colour naming

In computer vision, colour naming has been posed as a fuzzy‐set problem where each colour category is modeled by a function that assigns a membership value to any given sample. However, the success in the automation of this process relies on having an appropriate psychophysical data set for this purpose. In this article we present a data set obtained from a colour‐naming experiment. In this experiment, we used a scoring method to collect a set of judgments adequate for the fuzzy modeling of the colour‐naming task. The data set is composed of 387 colour reflectances, their CIELab and Munsell values, and the corresponding judgments provided by the subjects in the experiment. These judgments are the membership values to the 11 basic colour categories proposed by Berlin and Kay (Berlin B, Kay P. Berkeley: University of California; 1969). All these data have been made available online ( http://www.cvc.uab.es/color_naming ) and, in this article we provide a wide analysis of them. To prove the suitability of the proposed scoring methodology, we have computed a set of common statistics in colour‐naming experiments, such as consensus and consistency, on our data set. The results make it possible for us to conclude the coherence of our data with previous experiments and, thus, its usefulness for the fuzzy modeling of colour naming. © 2005 Wiley Periodicals, Inc. Col Res Appl, 31, 48–56, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20172     

Predicting visual similarity between colour palettes

This work is concerned with the prediction of visual colour difference between pairs of palettes. In this study, the palettes contained five colours arranged in a horizontal row. A total of 95 pairs of palettes were rated for visual difference by 20 participants. The colour difference between the palettes was predicted using two algorithms, each based on one of six colour-difference formulae. The best performance (r² = 0.86 and STRESS = 16.9) was obtained using the minimum colour-difference algorithm (MICDM) using the CIEDE2000 equation with a lightness weighing of 2. There was some evidence that the order (or arrangement) of the colours in the palettes was a factor affecting the visual colour differences although the MICDM algorithm does not take order into account. Application of this algorithm is intended for digital design workflows where colour palettes are generated automatically using machine learning and for comparing palettes obtained from psychophysical studies to explore, for example, the effect of culture, age, or gender on colour associations.     

A study of colour emotion and colour preference. Part I: Colour emotions for single colours

This article classifies colour emotions for single colours and develops colour‐science‐based colour emotion models. In a psychophysical experiment, 31 observers, including 14 British and 17 Chinese subjects assessed 20 colours on 10 colour‐emotion scales: warm–cool, heavy–light, modern–classical, clean–dirty, active–passive, hard–soft, tense–relaxed, fresh–stale, masculine–feminine, and like–dislike. Experimental results show no significant difference between male and female data, whereas different results were found between British and Chinese observers for the tense–relaxed and like–dislike scales. The factor analysis identified three colour‐emotion factors: colour activity, colour weight, and colour heat. The three factors agreed well with those found by Kobayashi and Sato et al. Four colour‐emotion models were developed, including warm–cool, heavy–light, active–passive, and hard–soft. These models were compared with those developed by Sato et al. and Xin and Cheng. The results show that for each colour emotion the models of the three studies agreed with each other, suggesting that the four colour emotions are culture‐independent across countries. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 232–240, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20010     

Age effects on colour emotion,preference, and harmony

Two psychophysical experiments were carried out to investigate whether or not colour emotion responses would change with the advance of the viewer's age. Two forms of stimuli were used: 30 single colours (for Experiment 1) and 190 colour pairs (for Experiment 2). Four word pairs, warm/cool, heavy/light, active/passive, and like/dislike, were used to assess colour emotion and preference in Experiment 1. In Experiment 2, harmonious/disharmonious was also used in addition to the four scales for Experiment 1. A total of 72 Taiwanese observers participated, including 40 (20 young and 20 older) for Experiment 1 and 32 (16 young and 16 older) for Experiment 2. The experimental results show that for single colours, all colour samples were rated as less active, less liked, and cooler for older observers than for young observers. For colour combinations, light colour pairs were rated as less active and cooler for older observers than for young observers; achromatic colour pairs and those consisting of colours in similar chroma were rated as cooler, less liked and less harmonious for older observers than for young observers. The findings may challenge a number of existing theories, including the adaptation mechanism for retaining consistent perception of colour appearance across the lifespan, the modeling of colour emotion based on relative colour appearance values, and the additive approach to prediction of colour‐combination emotion. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2011     

Testing uniform colour spaces and colour‐difference formulae using printed samples

A grey‐scale psychophysical experiment was carried out for evaluating colour differences using printed colour patches. In total, 446 pairs of printed samples were prepared surrounding 17 colour centers recommended by the CIE with an average δE of 3 units. Each pair was assessed 27 times by nine observers. The visual results were used to test some selected more advanced colour‐difference formulae and uniform colour spaces. The results showed that CIELAB and OSA performed the worst, and the advanced formulae and spaces gave quite satisfactory performance such as CIEDE2000, CIE94, DIN99d, CAM02‐UCS, and OSA‐GP‐Eu. The colour discrimination ellipses were used to compare with those of the earlier studies. The results showed that they agreed well with each other. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2012     

Investigation of texture effect on visual colour difference evaluation

The texture effect on visual colour difference evaluation was investigated in this study. Five colour centers were selected and textured colour pairs were generated using scanned textile woven fabrics and colour‐mapping technique. The textured and solid colour pairs were then displayed on a characterized cathode ray tube (CRT) monitor for colour difference evaluation. The colour difference values for the pairs with texture patterns are equal to 5.0 CIELAB units in lightness direction. The texture level was represented by the half‐width of histogram, which is called texture strength in this study. High correlation was found between texture strength and visual colour difference for textured colour pairs, which indicates that an increasing of 10 units of texture strength in luminance would cause a decreasing of 0.25 units visual difference for the five colour centers. The ratio of visual difference between textured and solid colour pairs also indicates a high parametric effect of texture. © 2005 Wiley Periodicals, Inc. Col Res Appl, 30, 341–347, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.     

Computational production of colour harmony. Part 1: A prototype colour harmonization tool

Although web page and computer interface developers generally have little experience in generating effective colour schemes, colour selection appears rarely in user interface design literature, and there are few tools available to assist in appropriate choice of colours. This article describes an algorithmic technique for applying colour harmony rules to the selection of colour schemes for computer interfaces and web pages. Our software implementation of this approach—which we term the Colour Harmoniser—adapts and extends classical colour harmony rules for graphical user interfaces, combining algorithmic techniques and personal taste. A companion article presents the experimental evaluation of the system presented here. Our technique applies a set of rules for colour harmony to specific features of the interface or web page to create abstract colour schemes; the user then modifies the overall colour cast, saturation, and light–dark distribution, producing colourings that are both harmonious and usable. We demonstrate experimentally that the software is relatively simple to use and produces colourings that are well‐received by humans. In this article, we define a fitness function that numerically evaluates the colour harmony of a user interface and underpins a genetic algorithm for creating harmonious schemes. We show how abstract, hue‐independent, colour schemes may be mapped to real colour schemes, leaving the abstract colour harmony unchanged, but accommodating the developer's personal preferences for overall colouring, light–dark contrast, and saturation. This abstract/concrete separation automates the creation of harmonious schemes and allows unskilled developers to express their aesthetic preferences using simple direct manipulation controls. © 2011 Wiley Periodicals, Inc. Col Res Appl, 38, 203–217, 2013.     

Computational production of colour harmony. Part 2: Experimental evaluation of a tool for gui colour scheme creation

Although webpage and computer interface designers generally have little experience at generating effective colour schemes, colour selection appears only rarely in user interface design literature. This article describes the experimental evaluation of an algorithmic technique that applies colour harmony rules to the selection of colour schemes for computer interfaces and web pages. The technique uses a genetic algorithm to evolve colour schemes; the evolutionary path is determined by a quantitative colour harmony evaluation function. Our technique first creates abstract colour schemes by applying those rules to specific features of the interface or web page; the user then holistically modifies the scheme's overall colour cast, overall saturation, and light–dark distribution, producing colourings that are both harmonious and usable. We demonstrate experimentally that the software is relatively simple to use and produces colourings that are well‐received by humans. In an earlier article, the criteria for a colour harmony tool for computer interfaces and websites were described and used in the design of the Colour Harmoniser, our software implementation of a system that is based on classical rules of colour harmony, adapted and extended to suit graphical user interfaces. In this article, we describe two sets of experiments that have demonstrated the usability and effectiveness of the Colour Harmoniser tool, compared with standard methods of colour selection. These experiments suggest that the tool functions somewhat more effectively than we originally anticipated, producing colour schemes that were rated more highly on several quality scales than those produced by random choice, by humans who self‐classify as nonartists, and by humans who self‐classify as artists. © 2011 Wiley Periodicals, Inc. Col Res Appl, 38, 218–228, 2013.     

Analysis of experiments to determine individual colour preference

Finding an efficient way to understand individual colour preference is important to researchers and designers. This article compares three research strategies to test individual colour preference including two research experimental environments (online and laboratory) and two research methods (multiple choice for N‐alternative‐forced‐choice and multiple choice for rank‐order). Three psychophysical experiments have been carried out. Participants were presented with six colour patches (red, orange, yellow, green, blue, and purple) arranged in a random order on a computer display. In the first two experiments (Online experiment and Laboratory experiment I), participants were asked to indicate which colour square they prefer most; in the third experiment (Laboratory experiment II), participants were asked to rank their colour preferences of the six colour patches. The similarity between the results obtained from two experimental environments provides some validation for the online protocol and suggests that online experiments could be used more often. Pairwise comparisons for individual colour preference between genders and nationalities were carried out, and it was found that male and female responses were significantly different; but there was no statistical significance between Chinese and UK participants. The results from Monte Carlo simulations suggested that the rank‐order method should be preferred for individual colour preference studies involving small numbers of participants (especially less than 15 participants).     

A cross‐cultural comparison of colour emotion for two‐colour combinations

Psychophysical experiments were conducted in the UK, Taiwan, France, Germany, Spain, Sweden, Argentina, and Iran to assess colour emotion for two‐colour combinations using semantic scales warm/cool, heavy/light, active/passive, and like/dislike. A total of 223 observers participated, each presented with 190 colour pairs as the stimuli, shown individually on a cathode ray tube display. The results show consistent responses across cultures only for warm/cool, heavy/light, and active/passive. The like/dislike scale, however, showed some differences between the observer groups, in particular between the Argentinian responses and those obtained from the other observers. Factor analysis reveals that the Argentinian observers preferred passive colour pairs to active ones more than the other observers. In addition to the cultural difference in like/dislike, the experimental results show some effects of gender, professional background (design vs. nondesign), and age. Female observers were found to prefer colour pairs with high‐lightness or low‐chroma values more than their male counterparts. Observers with a design background liked low‐chroma colour pairs or those containing colours of similar hue more than nondesign observers. Older observers liked colour pairs with high‐lightness or high‐chroma values more than young observers did. Based on the findings, a two‐level theory of colour emotion is proposed, in which warm/cool, heavy/light, and active/passive are identified as the reactive‐level responses and like/dislike the reflective‐level response. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2012