On the colours dichromats see

Dichromatic colour vision is commonly believed to be a reduced form of trichromatic colour vision (referred to as the reductionist principle). In particular, the colour palette of the dichromats is believed to be a part of the colour palette of the trichromats. As the light‐colour palette differs from the object‐colour palette, the dichromatic colour palettes have been derived separately for light‐colours and object‐colours in this report. As to light‐colours, the results are in line with the widely accepted view that the dichromatic colour palettes contain only two hues. However, the dichromatic object‐colour palettes have proved to contain the same six component colours which constitute the trichromatic object‐colour palette (yellow, blue, red, green, black and white). Moreover, all the binary and tertiary combinations of the six component colours present in the trichromatic object‐colour palette also occur in the dichromatic object‐colour palettes. Yet, only five of the six component colours are experienced by dichromats as unitary (unique) object‐colours. The green unitary colour is absent in the dichromatic object‐colour palettes. The difference between the dichromatic and trichromatic object‐colour palettes arises from the fact that not every combination of the component‐colour magnitudes occurs in the dichromatic object‐colour palettes. For instance, in the dichromatic object‐colour palettes there is no colour with the strong green component colour. Furthermore, each achromatic (black or white) component colour of a particular magnitude is combined with the only combination of the chromatic components. In other words, the achromatic component colours are bound with the chromatic component combinations in dichromats. © 2012 Wiley Periodicals, Inc. Col Res Appl, 39, 112–124, 2014     

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     

A computer‐assisted colour selection system based on aesthetic measure for colour harmony and fuzzy logic theory

An aesthetic measure based approach for constructing a colour design/selection system is proposed in this article. In this model, an image data base for the relationships between the psychological preference of customers and clothing colour tones is built using the membership functions of a fuzzy set, and an aesthetic measure calculation method based on colour harmony is also proposed. In addition, a skin colour detection theory is proposed to construct a skin colour detection program to detect the skin colour of a customer, which is then taken as the major colour in matching the skin, polo shirt, and(or) pant colours to select the best colour combination. Integrating the skin colour detection theory, colour harmony theory, aesthetic measure method, and fuzzy set theory, a program is constructed to build an aesthetic measure based colour design/selection system. With the aid of this system, one can get proper cloth colours to match his/her skin colour and image requirement by starting with inputting one's colour photo, catching image with a camera, or inputting R, G, B values of his/her skin. The theoretical results for the ranks of clothing colours proposed by the system are examined with the experimental results and the result shows they are very close, suggesting that the proposed colour selection system is acceptable. Although the selection of clothing colours is taken as an example to specify the methodology, it can also be used to develop a system for other products. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 411–423, 2008     

A method for exploring word-colour associations

Strong associations exist between colours and concepts or words. Understanding these associations, sometimes referred to as colour emotions, is important for effective use of colour in art and design. Traditionally the relationships have been systematically explored in experiments where participants scale colours according to bipolar adjectives such as warm-cool. In this article, a method for exploring the relationships between words and colours is suggested and is demonstrated. A psychophysical experiment is described where participants select colours based on words. The data are used to show that many similarities between the word-colour relationships for UK and Chinese participants although some interesting differences are also revealed. The method makes explicit the observation that there is not a one-to-one relationship between words and colours. The method could be used to explore word-colour relationship for specific words and participant groups or could be used to generate ground-truth data for testing methods for automatically generating the word-colour relationships.     

Colour category foci of Munsell colour spectra revealed by two computational methods

Colour names and psychophysical colour categories play an important role on human communication. For several application areas from computer vision to Internet shopping, it would be useful to manage colour information using methods of computational colour naming in a similar manner as people do in their everyday life. In this study, we applied two computational methods, the nonnegative matrix factorization and self‐organizing maps, to derive basic colours from a spectral database of Munsell colours, and a subset of it. The subset was generated to include only the most saturated samples of each Munsell Hue and Munsell Value pair of the original database. Using both the methods and both the databases, we calculated the sets of 3, 4, 6, and 8 basis vectors to represent the focal colours of colour categories. Colour names of the calculated focal colours were investigated using the results by Sturges and Whitfield as a reference. Nonnegative matrix factorization yields calculated colours more compatible with human basic colours, but the spectra generated by self‐organizing maps are more similar to natural spectra as their shape is smoother. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2010     

Testing LED lighting for colour discrimination and colour rendering

Light‐emitting diode (LED) technology offers the possibility of obtaining white light, despite narrow‐band spectra. In order to characterize the colour discrimination efficiency of various LED clusters, we designed a classification test, composed of 32 caps equally distributed along the hue circle at about 3 ΔE* _ab‐unit intervals. Forty normal colour observers were screened under four different LED test light sources adjusted for best colour rendering, and under one control incandescent light of the same colour temperature. We used commercially available red, green, blue, and/or amber LED clusters. These yielded a poor colour rendering index (CRI). They also induced a significantly higher number of erroneous arrangements than did the control light. Errors are located around greenish‐blue and purplish‐red shades, parallel to the yellow‐axis direction, whereas when the distribution of light covers the full spectrum, the LED clusters achieve satisfactory colour discrimination efficiency. With respect to the lights we tested, the colour discrimination is correlated with the CIE CRIs as well as with a CRI based on our sample colours. We stress the fact that increasing the chroma of samples by lighting does not necessarily imply an improvement of colour discrimination. © 2008 Wiley Periodicals, Inc. Col Res Appl, 34, 8–17, 2009.     

Cross‐regional comparison of colour emotions Part II: Qualitative analysis

During the colour perception process, an associated feeling or emotion is induced in our brains, and this kind of emotion is known as colour emotion. In Part I of this study, a quantitative analysis of the cross‐regional differences and similarities of colour emotions as well as the influence of hue, lightness, and chroma on the colour emotions of the subjects from Hong Kong, Japan, and Thailand, was carried out. In Part II, colour emotions of the subjects in any two regions were compared directly using colour planners showing the effect of the lightness and the chroma of colours. The colour planners can help the designers to understand the taste and feelings of the target customers and facilitate them to select suitable colours for the products that are intended to be supplied in different regions. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 458–466, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20063     

Colour meaning and consumer expectations

Deciding a colour for a product is a significant task for designers to attract consumer attention and communicate brand messages. It requires an initial analysis that explores consumer expectations within the sector, and this information is then used to inform development of a product design. This article discusses the application of the product colour development process during the initial phase of product design. Using a case study approach, one particular product category—a dishwashing liquid product was selected based on the suggestion from a leading U.K. consumer goods manufacturing company that colour is a major design factor for this product category. In the first phase of the study, interviews and an online survey were carried out with consumers (to explore what elements are important when they purchase a washing‐up liquid product). In the second phase of the study, a colour meaning experiment was conducted to explore possible colours for dishwashing liquid packaging using a semantic differential method. The results show that yellowish and bluish green colours evoke positive responses while saturated and dark green colours are perceived more negatively.     

The role of individual colour preferences in consumer purchase decisions

The purpose of this study is to test whether consumers' personal colour preferences (in an abstract sense rather than for a particular product) affect their intended product purchase decisions if they are given various colour choices. This work employs two experiments with visual components to investigate which colour a participant would choose if asked to select a product to purchase when there is a range of colours available. Two experiments were also designed to elicit a response about which colour each participant prefers (in an abstract sense). The study finds that personal colour preferences affect intended product‐colour purchase decisions but that the extent of this varies from one product category to the next. Further analysis reveals that personal colour preferences are secondary to factors such as colour functionality and colour performance. This work presents new experimental data about the role of colour in product and product packaging on intended consumer purchase decisions. A conceptual framework, supported by the experimental findings, are understanding the relationship between individual colour preferences and product‐choice colours, and more functional aspects of colour itself (such as the effect of colour on product's performance or functionality).     

Colour memory for various sky,skin, and plant colours: Effect of the image context

In memory‐matching techniques, the remembered colour might differ from the original colour even if the viewing situation is the same. Our aim was to point out whether these so‐called memory shifts are significant in the everyday situations of viewing photos depicting sky, skin, or plant, or viewing standalone uniform colour patches of sky, skin, or plant colours. In many cases, significant memory shifts have been found. Considering only one type of object (sky or skin or plant), memory shifts turned out to be systematic in the sense that they were directed toward specific intervals of hue, chroma, and lightness. This tendency was more explicit for photos than for standalone colour patches. A method to quantify prototypical colours and their tolerance bounds was suggested. © 2001 John Wiley & Sons, Inc. Col Res Appl, 26, 278–289, 2001     

User evaluation of a virtual colour laboratory as a tool for demonstrating colour appearance

The aim with our research is to contribute to a better understanding of how colour research findings can be conveyed to a broader target audience, using digital media. This article presents a user study focusing on the popular science project the Virtual Colour Laboratory (VCL). The VCL is an interactive webpage for presenting and demonstrating existing research results on spatial colour phenomena. It was initiated and carried out with the intention of spreading knowledge of colour appearance and colour perception to a wider target audience, from the viewpoint of practice based architectural colour research. The VCL enables the user to investigate actively how colours appear in different situations, and provides information on relevant literature and links for further studies. In a questionnaire study, carried out in 2014, two groups of users including architecture students and professionals within architecture, art and design evaluated the usability of the VCL with a combination of qualitative and quantitative methods. The predominant result showed that the VCL generally was highly appreciated. However, the results also show differences in how the two groups experienced the visual and written content of the stations in the VCL, as well as differences in how they experienced the VCL as a whole. This highlights the importance of adjusting levels of information depending on the target group, as well as presents advantages and difficulties of showing research on spatial colour appearance on the web using digital visualization as a medium for presentation. © 2015 Wiley Periodicals, Inc. Col Res Appl, 41, 611–625, 2016     

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     

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     

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.     

Colour in folklore and tradition—The principles

Human beings use colour to manipulate their personal appearance and environment. A large part of this usage falls within the area of oral tradition and ritual that have been handed down within families, tribes or geographical areas. The resulting images are part of our culture; they are activities that give us feelings of belonging and of doing the ‘right thing’. Two surveys were designed to learn more of these very human activities. The first centered on Britain and Ireland; the other was international. Three major driving forces were found for the use of colour in folklore and symbolism—economic, historical and social. The Principle of Adaptation of Physical Resources accounts for the choice of mourning colours of most countries. Colour usage in death echoes the three approaches to mourning of sadness, joy (for the life of the dead), and fear of the spirits of the dead. The Principle of Adaptation of Ideas accounts for regional variations in colour folklore. This embodies a Darwinian‐type principle of behavior, that is, “to survive within a community a belief must have relevance to that community.” A major principle of folk medicine involving colour is the Principle of curing like with like. There are four Principles of Colour Selection in folklore—by the contrast displayed, as a transfer from the perceived or actual usefulness of the colour, by association, and by availability. Green above all colours has especial significance both in the UK and Ireland. In everyday language it is the Principle of Singularity that controls use of colour words as symbols. The biological mechanism permitting these many and contrasting uses of colour depends on the fact that colour is a perception, not the property of an object. That is, a colour can ‘mean’ whatever we wish it to ‘mean’. © 2003 Wiley Periodicals, Inc. Col Res Appl, 29, 57–66, 2004; Published online in Wiley Interscience (www.interscience.wiley.com). DOI 10.1002/col.10212     

Cross‐regional comparison of colour emotions Part I: Quantitative analysis

Colour emotion is a feeling or emotion induced in our brains when we look at a colour. In this article, the colour emotional responses obtained by conducting visual experiments in different regions, namely Hong Kong, Japan and Thailand, using a set of 218 colour samples are compared using a quantitative approach in an attempt to study the influence of different cultural and geographical locations. Twelve pairs of colour emotions described in opponent words were used. These word pairs are warm–cool, light–dark, deep–pale, heavy–light, vivid–sombre, gaudy–plain, striking–subdued, dynamic–passive, distinct–vague, transparent–turbid, soft–hard, and strong–weak. These word pairs represent the fundamental emotional response of human beings toward colour. The influences of lightness and chroma were found to be much more important than that of the hue on the colour emotions studied. Good correlations of colour emotions among these three regions in East Asia were found, with the best ones for colour emotion pairs being light–dark and heavy–light. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 451–457, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20062     

Colour and tolerance of preferred skin colours on digital photographic images

Skin‐tone has been an active research subject in photographic colour reproduction. There is a consistent conclusion that preferred skin colours are different from actual skin colours. However, preferred skin colours found from different studies are somewhat different. To have a solid understanding of skin colour preference of digital photographic images, psychophysical experiments were conducted to determine a preferred skin colour region and to study inter‐observer variation and tolerance of preferred skin colours. In the first experiment, a preferred skin colour region is searched on the entire skin colour region. A set of nine predetermined colour centers uniformly sampled within the skin colour ellipse in CIELAB a*b* diagram is used to morph skin colours of test images. Preferred skin colour centers are found through the experiment. In a second experiment, a twice denser sampling of nine skin colour centers around the preferred skin colour center determined in the first experiment are generated to repeat the experiment using a different set of test images and judged by a different panel of observers. The results from both experiments are compared and final preferred skin colour centers are obtained. Variations and hue and chroma tolerances of the observer skin colour preference are also analysed. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2013     

Asymmetric colour matching: Memory matching versus simultaneous matching

We have compared corresponding pairs obtained by simultaneous matching (haploscopic matching) and by memory matching (after 10 min) using 34 reference tests selected from the Munsell Atlas (glossy), belonging to the four main hues 5Y, 5G, 5PB, and 5RP. These colours lie very close to the F₁ and F₂ axes in the SVF space, where we have analyzed our results. Illuminants D65 and A were used as reference and matching illuminants, respectively. Our results show for both kinds of matching a tendency to select more colourful colours than the original ones, with significant differences between matching and test colours, whereas hue does not seem to follow a definite pattern. This behavior is similar to that found in colour‐matching experiments without illuminant changes. The analogy does not hold for lightness, which in the present experiment does not seem to follow a clear pattern. The best matching colours lie along the red‐green axis and the worst matching colours along the blue‐yellow axis. © 2001 John Wiley & Sons, Inc. Col Res Appl, 26, 458–468, 2001     

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     

Colour-emotion association and colour preference for elder care robot appearance

With the population ageing in Taiwan, it is projected that elder care robots incorporating smart technologies will play an essential role in ambient assisted living. This research has two purposes: (1) to investigate whether older adults' colour-emotion associations and colour preferences for robot appearance affect their perceptual judgements; and (2) to explore gender differences in their judgements. Phase I of this research uses a questionnaire to investigate 91 participants' preferences for robot style and their emotional trigger words for the role of robots. Phase II experiments were performed on another 60 older adults to identify whether their colour-emotion associations and colour preferences affect their perceptual judgements. The research results show that, regardless of gender difference, participating older adults prefer a robot with non-human–like features. The results also show that there is no significant difference between males and females in terms of the effect of colour-emotion association on a robot's appearance. Older adults tend to associate warm colours with emotional semantics, such as friendly, comfortable, reassuring, gentle and lively. Preferred colours include red, white and yellow. Black and grey are almost never preferred by older adults. There are significant differences by gender in the preferences for the colours white and purple. Older females prefer purple more, while white is preferred by older males. For the other colours, there were no significant differences between males and females. Colour attributes do not have any effect on colour-emotion association, whereas colour preference is highly positively correlated with b*.