The usability of the CIE colour‐matching functions in the case of CRT monitors

During the past years, several papers have been published that question the use of the CIE colour‐matching functions in the case of metameric samples. Visually matching samples produced on CRT (Cathode Ray Tube) monitors are metameric to most colour stimuli created by illuminating reflecting materials. As CRT monitors are often used in colour design applications, it seemed important to check how well CIE colorimetry will predict such colour matches. To investigate this problem, we set up an experiment in which painted samples were matched with samples produced on a CRT monitor. The colour of incandescent lamp irradiated Munsell samples were visually matched to the mixture of the RGB primaries of a CRT monitor. Both the reflected colour stimuli of the Munsell samples and the emitted stimuli of the monitor were measured spectroradiometrically. Our results imply that there is an observer‐dependent variability among the matches, but we could not find a major difference between the tristimulus data of the hard copy and soft copy presentations that would indicate errors in the CIE colour‐matching functions. The measurement accuracy, quantization errors of the monitor, and the achieved accuracy of the colour matches are treated in this study. © 2001 John Wiley & Sons, Inc. Col Res Appl, 26, 436–441, 2001     

Unique hue data for colour appearance models. Part I: Loci of unique hues and hue uniformity

Psychophysical experiments were conducted to assess unique hues on a CRT display for a large sample of colour‐normal observers (n = 185). These data were then used to evaluate the most commonly used colour appearance model, CIECAM02, by transforming the CIEXYZ tristimulus values of the unique hues to the CIECAM02 colour appearance attributes, lightness, chroma and hue angle. We report two findings: (1) the hue angles derived from our unique hue data are inconsistent with the commonly used Natural Color System hues that are incorporated in the CIECAM02 model. We argue that our predicted unique hue angles (derived from our large dataset) provide a more reliable standard for colour management applications when the precise specification of these salient colours is important. (2) We test hue uniformity for CIECAM02 in all four unique hues and show significant disagreements for all hues, except for unique red which seems to be invariant under lightness changes. Our dataset is useful to improve the CIECAM02 model as it provides reliable data for benchmarking. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2011     

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.     

Evaluation of the crispening effect using CRT‐displayed colour samples

In this study, the crispening effect was clearly observed when 38 neutral‐coloured sample pairs with only lightness differences were assessed under 5 neutral backgrounds of different lightness values. The sample pairs are CRT‐based colours, and they are selected along the CIELAB L* axis from 0 to 100. The magnitude of colour difference of each pair is 5.0 CIELAB units. The visual assessment results showed that there is a very large crispening effect. The colour differences of the same pair assessed under different backgrounds could differ by a factor of up to 8 for a sample pair with low lightness. The perceived colour difference was enlarged when the lightness of a sample pair was similar to that of the background. The extent of crispening effect and its quantification are discussed in this investigation. The performances of five colour‐difference equations were also tested, including the newly developed CIEDE2000. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 374–380, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20045     

Some aspects of the visual scaling of large colour differences

The formulation of a metric to provide numbers that correlate with visually perceived colour differences has proved a very difficult task. Most early experimental work was concerned with just-perceptible colour differences. Later the concept of perceptibility was expanded to acceptability, it being argued that many industrial tolerances were larger than just-perceptible. This led naturally to the concept of large colour differences and the question as to whether the current CIE colour-difference formulae, specified as appropriate for just-perceptible differences, can be applied to larger differences than those concerned with, for instance, colour matches experienced in the fabric dyeing industry. This article investigates the application of four colour-difference formulae to visual scaling of large colour differences between photographically prepared reflection colour samples at approximately constant lightness. It is shown that the scaling of colour differences depends on the directions of hue and chroma differences of a test sample when compared with a reference. It is also shown that, of the four candidate colour-difference metrics, the modified CIE 1976 L*a*b* colour difference, referred to as CIE1994 or , correlates best with visual scaling. © 1997 John Wiley & Sons, Inc. Col Res Appl, 22, 298–307, 1997     

Interrelation of the Swiss Colour Atlas (SCA-2541) and the Munsell Color Order System

The CIE tristimulus values of measured Swiss Colour Atlas samples were converted to Munsell notations using a colour notation conversion program. A selected subset of SCA-2541 sample points was chosen: the samples on the fully populated regularly spaced hues 6, 12, 18, 24, 30, 36, 42, 48, 54, and 60. The resulting Munsell notations were plotted onto Munsell Value-Chroma and Hue-Chroma planes and analysed for regularity of spacing and hue distribution around the achromatic axis. An earlier article has detailed the interrelation between the Natural Color System (NCS) and the Munsell Color Order System using similarly constructed charts. Comparison is made with the sample spacing of the NCS and SCA-2541 points when mapped into Munsell colour space, to determine similarities and differences between these two geometrically similar systems; both are double cones forming equilateral triangular constant hue planes. © 1997 John Wiley & Sons, Inc. Col Res Appl, 22, 111–120, 1997     

Requirements capture for colour information for design professionals

This article presents the results of a study that investigates the status of colour information use in the design process and generates ideas for a colour tool. Face‐to‐face interviews with senior designers and brand managers from the packaging and branding fields were conducted as the primary data collection method. The results are categorized into six topics: colour decision, types of colour information considered to be important in the design process, reasons for considering colour information important in the design process, current use of colour information, design professionals' preferences for existing colour tool types and data types and suggestions for a colour tool. It is concluded that there are problems with existing colour resources and tools regarding their availability and usefulness; there is a strong demand for a colour tool in the packaging design and branding processes. The insight from this work will help researchers, design professionals and colour tool developers to make informed decisions on the areas on which they should focus, how they should do so and why. This will facilitate better provisions and uptake of useful colour information for design professionals in the design process and strategy fields.     

The LLAB (l:c) colour model

A new colour model, named LLAB(l:c) is derived. It includes two parts: the BFD chromatic adaptation transform derived by Lam and Rigg, and a modified CIELAB uniform colour space. The model's performance was compared with the other spaces and models using the LUTCHI Colour Appearance Data Set. The results show that LLAB(l:c) model is capable of precisely quantifying the change of colour appearance under a wide range of viewing parameters such as light sources, surrounds/media, achromatic backgrounds, sizes of stimuli, and luminance levels. It had a similar performance as that of the Hunt colour appearance model. The LLAB(l:c) model was also tested using various colour difference datasets. The model gave a similar performance as the state-of-the-art colour difference formulae such as CMC, CIE94, and BFD. This performance is considered to be very satisfactory, and the model, therefore, should be considered for field trials in applications such as colour specification, colour difference evaluation, cross-image reproduction, gamut mapping, prediction of metamerism and colour constancy, and quantification of colour-rendering properties. The model does not give predictions for chroma (as distinct from colourfulness), or for brightness, and it does not include any rod response. © 1996 John Wiley & Sons, Inc.     

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.     

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     

The Specification of Colour Appearance. II. Effects of Changes in Viewing Conditions

The effects on colour appearance of changes in surround, illuminant colour, absolute luminance level, and field size are considered. Methods are discussed whereby existing formulae can be used or modified, and new formulae devised, to obtain measures that correlate with the colour attributes involved. Examples of the application of such formulae to practical problems in illuminating engineering and in television are considered briefly. (In Part I the basic concepts and terms necessary for the specification of colour were considered.)     

Geometric relations between scales of small colour differences

Varying magnitude of colour differences from threshold up to moderate size in painted sample pairs at five CIE colour centers was estimated by grey scale assessment. Painted samples were produced for constant step width along the main axes of previously determined threshold (x,y,Y)‐ellipsoids with lightness variation at constant (x,y)‐chromaticity starting with threshold length and enlarging it five times for moderate magnitude of colour difference. Pairs were formed for linear extensions along axes and for diagonal combinations at equal step width between axes. The model under test assumes additive linear scale extension in constant proportions of the threshold (x,y,Y)‐ellipsoid for increasing magnitude of perceived colour difference and correlates perceptual main colour characters with main ellipsoid axes. Both assumptions were falsified to some degree: in general, magnitude of colour difference varies differently, though close to linear, and slightly subadditive for the three axes and for the different colour centers; the short (x,y)‐ellipse axis in some cases is not correlated with a perceptual hue vector component, and the main lightness direction sometimes is tilted in relation to the (x,y)‐plane. Three colour‐difference formulae do not provide better global predictions than the local (x,y,Y)‐ellipsoid formulae. The results may be used for more detailed modeling of colour‐difference formulae and for tolerance settings at different ranges of colour difference. © 1999 John Wiley & Sons, Inc. Col Res Appl, 24, 78–92, 1999     

Colour correctability of a colour-matching recipe

The colour of a test dyeing/batch is frequently too far from the target colour to be accepted and some correction to the component concentrations in the recipe is needed. Therefore, it would be useful for a colourist, already at the time of match prediction, to have some a priori information about the possibility of correcting the colour of a particular recipe. In this article, the definitions of directional and overall colour correctability are introduced and the way to calculate their numerical estimates is developed. These values enable the comparison of the colour correctability of various different recipes for the same target colour in advance. In addition, the link between the colour sensitivity and the colour correctability of a recipe is discussed. A numerical example is provided for illustration. © 1997 John Wiley & Sons, Inc. Col Res Appl, 22, 88–95, 1997     

A colour study approach through colour measurements on slides of art paintings

The present work deals with the problem of colorimetric fidelity of digitized colour slides representing fine art paintings. This consists of a comparison between colour measurements provided by spectrophotometry on fourteen original colour samples, which are uniformly painted square-shaped patches and those taken on digitized colour slides of the same colour samples. Digital acquisition of slides were performed by a 3CCD detector and a combination of colour correction filters. The obtained R_cam, G_cam, and B_cam values were then corrected and transformed into X_cam, Y_cam, and Z_cam values based on the CIE 1931 XYZ colorimetric system. The colour difference, , in the CMC uniform colour space is also calculated and found to be equal to seven, = 7, in average value, when colour compensating filters are used. This method is finally applied to four art works reproduced on different slides, and colour results were qualitatively compared as an indication to these resulting from Ostwald disk and saturation diagrams of previous research studies related to paintings that are created by the same artists. This comparison led to the same conclusions that were already proposed by the previous researchers. The results clearly demonstrate the contribution of the method to a computer-aided study of art works through image data banks that are realized by slides, taking into consideration, however, that this study consists of a first approach, offering a promising solution to the problem of colour accuracy of slides. © 1997 John Wiley & Sons, Inc. Col Res Appl, 22, 326–334, 1997     

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.     

Experiments to promote colour changes in wool

Wool colour is not stable and it changes during storage. This study developed wool challenge methods by using a one-week water bath incubation at 40°C or incubation overnight at a higher temperature to promote colour changes in wool. The study showed that the bacteria present in raw wool play a significant role in colour biodegradation during challenge (storage). A stable wool colour could be obtained for wool specification after a challenge treatment before colour measurement.     

The men who coloured Britain

Colour standards, initially for specification purposes (e.g., the Post Office, Railways, and the Military), were transformed in Britain during the 1970s into instruments for the pursuit of a Modernist agenda. Extolling a rational approach to colour, a master standard and a set of derived standards were devised at the British Standards Institution that would provide a colour palette covering the entire built environment of Britain. These revolutionized colour standards and were a unique venture in any country. This article charts the development of these standards, the problems to be overcome, and the role of their originators, Gloag, Hardy, and Medd. These little known figures had—and continue to have—a unique influence upon the colour of the built environment. Literally, they coloured Britain. And their standards remain in force today. © 2013 Wiley Periodicals, Inc. Col Res Appl, 39, 535–539, 2014     

Logo colour and differentiation: A new application of environmental colour mapping

Creating a logo design is an important task for a new company wishing to gain entry in a particular industry sector. It requires an initial situation analysis that examines existing logos within the sector, and this information is then used to inform creation of a new logo design. Colour, one of a number of design elements used to create a new logo, is a key element in creating a unique logo and in terms of enabling a logo achieve differentiation in a competitive environment. This article discusses the application of the environmental colour mapping process during the initial situation analysis phase of logo design. The process, which has been applied in urban design studies in Japan, America, France, England, and Norway has recently been augmented with the addition of digital technology. Using a case study approach, the ‘environment’ for the purpose of this study represented the logo designs of organizations within a specific industry sector. The main outcome from the process (colour data presented in the form of a colour map) was examined for patterns of similarity and dissimilarity and an attempt was made to identify new options for logo colours within the sector based on colour differentiation. This study represents a new application of the environmental colour mapping process and a number of limitations and benefits are discussed. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2011