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 harmony of two‐colour combinations using a 3D colour configuration

Over the past few years, although many studies have investigated colour harmony, most of those used the planar colour configuration, which is not in line with the design requirements of real‐life products. Therefore, this study used 11 basic colours and five types of colour scheme techniques to derive 141 colour combinations applied upon a physical 3D colour configuration to observe the phenomena of colour harmony. The results show that colour harmony on a 3D colour configuration is different from that on a planar colour configuration, and can be divided into four phenomena: (i) lightness difference was found to determine the colour harmony while achromatic colour was configured with achromatic colour; (ii) lightness sum prompted colour harmony while chromatic colour was configured with achromatic colour; (iii) lightness sum and chroma sum were found to determine colour harmony while chromatic colour was configured with chromatic colour with a two‐colour hue angle difference >90°; and (iv) lightness sum and hue difference were a determination of colour harmony while chromatic colour was configured with chromatic colour with a two‐colour hue angle difference of ≤90°. On the basis of these phenomena, this study develops a colour harmony model based on the colour parameters, most of which are derived from the addition of the colour attributes of two colours.     

Modelling of chromatic contrast for retrieval of wallpaper images

Colour remains one of the key factors in presenting an object and, consequently, has been widely applied in retrieval of images based on their visual contents. However, a colour appearance changes with the change of viewing surroundings, the phenomenon that has not been paid attention yet while performing colour‐based image retrieval. To comprehend this effect, in this article, a chromatic contrast model, CAMcc, is developed for the application of retrieval of colour intensive images, cementing the gap that most of existing colour models lack to fill by taking simultaneous colour contrast into account. Subsequently, the model is applied to the retrieval task on a collection of museum wallpapers of colour‐rich images. In comparison with current popular colour models including CIECAM02, HSI and RGB, with respect to both foreground and background colours, CAMcc appears to outperform the others with retrieved results being closer to query images. In addition, CAMcc focuses more on foreground colours, especially by maintaining the balance between both foreground and background colours, while the rest of existing models take on dominant colours that are perceived the most, usually background tones. Significantly, the contribution of the investigation lies in not only the improvement of the accuracy of colour‐based image retrieval but also the development of colour contrast model that warrants an important place in colour and computer vision theory, leading to deciphering the insight of this age‐old topic of chromatic contrast in colour science. © 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 361–373, 2015     

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     

Why higher resolution graphics cards are needed in colour vision research

The colour resolution of a 14‐bit and an 8‐bit per channel graphics card were evaluated and compared with the just noticeable difference between colours (varying only in luminance) for: (1) a standard observer (based on the CIE 1976 L*u*v* colour space) and (2) real observers in a colour discrimination task. The results of this study show that an 8‐bit per channel graphics card seems adequate for colour discrimination experiments where stimuli only vary in luminance. However, considering that the resolution of the graphics card should be equal to the Nyquist rate, an 8‐bit per channel card turns out to be inadequate. For colour discrimination experiments where stimuli only vary in chromaticity, there is an undersampling of the colour space with respect to MacAdam ellipses when using 8‐bit per channel graphics cards. The extremely fine colour resolution of a 14‐bit per channel graphics card overcomes these problems. Its use allows more accurate measurements of achromatic and chromatic discrimination thresholds and avoids experimental (spatial or luminance) artefacts, such as bandings that can occur on achromatic or chromatic gradients. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2011     

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     

Use of basic color terms by red–green dichromats: 1. General description

Abstract: In this article we present data comparing red–green dichromats' use of “Basic Color Terms” (BCTs) with that of standard trichromats. In a complementary article (Color Res Appl 2013) we use these data to evaluate two models of the mechanisms underlying dichromats' use of BCTs. There were three groups of observers—trichromats, protanopes, and deuteranopes—that each performed two tasks: “mapping” (which of these are exemplars of X?) and “best exemplar” (which is the best instance of X?), where X took the value of each Spanish BCT. The mapping task results were subjected to multidimensional scaling that revealed that dichromats differ from trichromats in the number and nature of the dimensions needed for describing BCTs' use. Trichromats required three dimensions closely related to the opponent color mechanisms (red–green, yellow–blue) and the light‐dark channel. In contrast, tridimensional solution for dichromats was difficult to interpret, whereas the fit for the bidimensional solution was very good and revealed a chromatic dimension, which did not match any of the trichromatic dimensions, and an achromatic one. There were also some error‐asymmetries (sometimes “A” was the predominant error when choosing exemplars of “B”, but not vice versa) and the groups differed in the frequency of use of some BCTs (e.g., protanopes chose more stimuli as orange than trichromats and deuteranopes). As expected, the best exemplar task produced more correct responses than the mapping task, and for both tasks, “primary” BCTs (black, white, red, green, yellow, and blue) produced better results than “derived” ones (brown, purple, orange, pink, and grey). © 2013 Wiley Periodicals, Inc. Col Res Appl, 39, 360–371, 2014     

Effect of observer metamerism on colour matching of display and surface colours

We studied the individual variability of asymmetric metameric colour matching between computer displays and object colour stimuli in conditions typical for the surface colour industries. Using two different computational techniques, we assessed the contribution of observer metamerism to this variability. In the studied conditions of spatially separated computer display and surface colour stimuli, this contribution was found to be insignificant for all colours but neutrals. In the chromaticness plane, the range of matches made by different observers practically coincides with the range of matches made by an individual observer. Consequently, we conclude that in the task of matching spatially separated display and surface colours, the range of matches made by a group of observers cannot be determined from variations in their colour‐matching functions, and thus the paradigm of the Standard Deviate Observer is shown to be inapplicable to the studied conditions. We suggest that individual variability in these conditions is governed by mechanisms of chromatic discrimination, and can be modeled by advanced colour difference formulae with suitably adjusted parametric coefficients. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 346–359, 2008     

A planar-vector based color space for graphic arts color analysis and reproduction

A new color space is developed, based on a model of a trigonally symmetric, planar arrangement of three response vectors, which first separates a visual stimulus via tristimulus values into achromatic and chromatic components and then recombines them. Because three visual response vectors are mutually opposed, the model is called the mutually opposed, trichromatic response (MOTR) model. The MOTR model does not introduce any new visual concepts but rather uses established concepts in an empirically different way. The MOTR model directly represents a color as a combination of two chromatic primaries and one achromatic primary. It is, therefore, particularly useful for halftone color reproduction based on two primary colors plus black, sometimes referred to as 100% GCR (gray component replacement). It is useful also because of its linearity properties between lightness and the chromatic and achromatic contents. The MOTR model's color space is applicable to existing color-order systems and provides a graphic representation often better than CIELAB and CIELUV do. The MOTR model is also consistent with many known visual characteristics such as unique hues, illuminant adaptation, wavelength discrimination, and defective color vision. The model as described herein is limited to the comparison of related colors under a given photopic luminance.     

Colour words and their uses

Popular usage of colour words as parts of speech obey certain rules according to whether they are population dependent and whether use demands a degree of colour vision. The word green refers to that colour most of us see, recognize and categorize as being of the colour called green. But, colours and colour words are to do with emotion as well as perception. What can we learn from the greatest writers, artists and musical composers; how do they, for example, regard green? From them we learn that we perceive colours with our ears as well as our eyes and, in an emotional sense, a colour word means or is associated with just what the writer intends. © 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 111–113, 2015     

Lightness and hue contrast effects in surface (fabric) colours

Simultaneous contrast effects on lightness and hue in surface colours were investigated. Test colours, surrounded by induction colours, were matched by colours surrounded by neutral gray. The matching colours were selected from a series of samples that varied in either lightness or hue respectively. The lightness experiments were carried out by a panel of 20 observers on 135 test/induction colour combinations. The hue experiments were conducted on 51 test/induction colour combinations by a panel of eight observers. The lightness of the test colour was found to decrease linearly with the lightness of the induction colour, regardless of the hue of the induction colour. The magnitude of the lightness contrast effect in fabric colours was found to be about one‐quarter of that found in CRT display colours in a previous study. The hue contrast effect found in this study followed the opponent‐colour theory. Two distinctly different regions could be identified when the hue difference was plotted against hue‐angle difference between the induction colour and the test colour. The slope of the line in the region where the hue of the induction colour is close to the test colour was much larger than the slope in the other region, indicating that the hue contrast effect was more obvious when the induction colour was close to the test colour. © 2006 Wiley Periodicals, Inc. Col Res Appl, 32, 55–64, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20285     

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     

Detection and modification of confusing color combinations for red‐green dichromats to achieve a color universal design

Color‐vision deficiency is a relatively common genetic condition, which often leads to the obstruction of necessary information in colored images. It is important to minimize such inconvenient effects in communication using colored images from a universal design perspective. The universal design principle stipulates that all environments and products should be usable by all people, regardless of age, physical attributes, and ability. This article proposes a method to detect color combinations in a given image that would confuse color dichromats, and suggests a way in which to modify them to make the image easily distinguishable for both normal and dichromatic observers. Confusing color combinations were detected based on a color‐difference calculation using simulations of how the color would appear to dichromats. The confusing colors were then modified based on the minimization of an evaluation function, which was defined as the sum of the degree of confusion and the degree of color change from the original image. Several colored images obtained by the proposed method were compared with the originals by red–green dichromatic observers who judged them to be clearer, thereby confirming that the proposed method was effective for color rendering for universal design. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 203–211, 2008     

Colour matching for ink-jet prints on paper

Predicting the colour of trichromatic prints by measuring the colour of the primaries and their areas has been shown to be possible using large area textile prints. This approach has been extended to paper printing with much smaller coloured areas, in a predetermined array of squares. As before, the light reflected from the coloured areas mixed additively within the integrating sphere of a spectrophotometer. Cyan, magenta, and yellow were used, with the addition of red, green, blue, and black, to simulate the typical situation likely to arise in commercial paper ink-jet printers. Partitive colour-mixing theory was used to predict the colours, and the results compared well with those obtained by measurement. However, unwanted overlaps of the printed coloured squares caused all the measured results to be darker and of higher chroma. The reverse process, whereby the area of each colour was calculated for a given target colour, specified by its tristimulus values, was also carried out. The results were generally in agreement with the actual number of squares used to produce the target, within one square out of 16. © 1998 John Wiley & Sons, Inc. Col Res Appl, 23, 18–26, 1998     

Spatial integration with chromatic stimuli in dichromatic vision

The critical area of spatial integration was examined in dichromatic vision (protanope and deuteranope) by means of chromatic thresholds at equiluminance. The results showed that the critical area became smaller as the chromatic saturation of the background field was increased. Here, the chromatic saturation was defined by the colorimetric purity of the background field, multiplied by the saturation coeficient (Cs) of each dominant wave-length. For the 470-nm field condition, the trend of dichromatic data was similar to that of the previous data with normal subjects. For the 590-nm condition, however, the decrease of integration area was less than that of the normal. This discrepancy can be attributed to the diference of saturation coeficients between normals and dichromats. © 1994 John Wiley & Sons, Inc.     

Defective Colour Vision. I–Its Nature

The various types of defective colour vision are described with particular reference to the sensations experienced. Two theories of colour vision, the trichromatic and opponent–colours theories, are described briefly and the recent objective proof of both is reviewed.     

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     

Geometric invariants under illuminant transformations

An object colour's Commission Internationale de l'Éclairage XYZ coordinates can change when it is viewed under different illuminants. The set of XYZ coordinates for all object colours, which is called the object‐colour solid, likewise varies under different illuminants. This article shows that, despite these changes, some properties are invariant under illuminant transformations. In particular, as long as the illuminant is nowhere zero in the visible spectrum, optimal colours take the same Schrödinger form, and no two optimal colours are metameric. Furthermore, all object‐colour solids have the same shape at the origin: they all fit perfectly into the convex cone (which we will call the spectrum cone) generated by the spectrum locus. The spectrum cone, itself, does not vary when the illuminant changes. The object‐colour solid for one illuminant can be transformed into the solid for another illuminant, by an easily visualized sequence of expansions and contractions of irregular rings, called zones. © 2012 Wiley Periodicals, Inc. Col Res Appl, 39, 179–187, 2014     

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.     

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