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.     

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 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     

A colour harmony model for two‐colour combinations

This study investigates harmony in two‐colour combinations in order to develop a quantitative model. A total of 1431 colour pairs were used as stimuli in a psychophysical experiment for the visual assessment of harmony. These colour pairs were generated using 54 colours selected systematically from CIELAB colour space. During the experiment, observers were presented with colour pairs displayed individually against a medium gray background on a cathode ray tube monitor in a darkened room. Colour harmony was assessed for each colour pair using a 10‐category scale ranging from “extremely harmonious” to “extremely disharmonious.” The experimental results showed a general pattern of two‐colour harmony, from which a quantitative model was developed and principles for creating harmony were derived. This model was tested using an independent psychophysical data set and the results showed satisfactory performance for model prediction. The study also discusses critical issues including the definition of colour harmony, the relationship between harmony and pleasantness, and the relationship between harmony and order in colour. © 2006 Wiley Periodicals, Inc. Col Res Appl, 31, 191–204, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20208     

A comparison of colour appearance for surface colours between outdoor and indoor environments

Psychophysical experiments of colour appearance, in terms of lightness, colourfulness, and hue, were conducted outdoors and indoors to investigate whether there was any difference in colour appearance between outdoor and indoor environments. A panel of 10 observers participated in the outdoor experiment, while 13 observers took part in the indoor experiment. The reference white had an average luminance of 12784 cd/m² in the outdoor experiment and 129 cd/m² in the indoor experiment. Test colours included 42 colour patches selected from the Practical Coordinate Color System to achieve a reasonable uniform distribution of samples in CIECAM02. Experimental results show that for both outdoor and indoor environments, there was good agreement between visual data and predicted values by CIECAM02 for the three colour appearance scales, with the coefficient of variation values all lower than 25 and the R² values all higher than 0.73, indicating little difference in the three dimensions of colour appearance between indoor and outdoor viewing conditions. Experimental data also suggest that the observers were more sensitive to variation in lightness for grayish colours than for highly saturated colours, a phenomenon that seems to relate with the Helmholtz-Kohlrausch effect. This phenomenon was modeled for predicting perceived lightness (J′) using the present experimental data. The new J′ model was tested using three extra sets of visual data obtained both outdoors and indoors, showing good predictive performance of the new model, with an average coefficient of variation of 14, an average R² of 0.88, and an average STRESS index of 14.18.     

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 comprehensive model of colour appearance for related and unrelated colours of varying size viewed under mesopic to photopic conditions

CIE has recommended two previous appearance models, CIECAM97s and CIECAM02. However, these models are unable to predict the appearance of a comprehensive range of colours. The purpose of this study is to describe a new, comprehensive colour appearance model, which can be used to predict the appearance of colours under various viewing conditions that include a range of stimulus sizes, levels of illumination that range from scotopic through to photopic, and related and unrelated stimuli. In addition, the model has a uniform colour space that provides a colour‐difference formula in terms of colour appearance parameters. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 293–304, 2017     

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.     

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     

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.     

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     

Quantifying colour appearance. part III. Supplementary LUTCHI colour appearance data

The experimental data from this study supplements the LUTCHI Colour Appearance Data as described in Part I of this paper. Two further experiments were carried out: one was to check conflicting results found previously, and another was to extend the range of luminance conditions used earlier. In addition, a brightness attribute was added to the original lightness, colourfulness, and hue scales for colour assessment. Experiment I results verified the uncertainties found previously in the comparison between luminous and nonluminous colours, and between the grey background results with and without a white border. Experiment II results revealed the changes in four perceived attributes under six quite different adapting luminances. The results were then used to test five uniform colour spaces and colour-appearance models used in Part II of this paper. Hunt's 91 model gave more accurate predictions of the experimental visual results, in comparison with the other spaces and models. Its predictive error for all attributes studied is within the accuracy of the typical observer.     

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     

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     

Mathematical approach for predicting non‐negative tristimulus values using the CAT02 chromatic adaptation transform

It has been reported that for certain colour samples, the chromatic adaptation transform CAT02 imbedded in the CIECAM02 colour appearance model predicts corresponding colours with negative tristimulus values (TSVs), which can cause problems in certain applications. To overcome this problem, a mathematical approach is proposed for modifying CAT02. This approach combines a non‐negativity constraint for the TSVs of corresponding colours with the minimization of the colour differences between those values for the corresponding colours obtained by visual observations and the TSVs of the corresponding colours predicted by the model, which is a constrained non‐linear optimization problem. By solving the non‐linear optimization problem, a new matrix is found. The performance of the CAT02 transform with various matrices including the original CAT02 matrix, and the new matrix are tested using visual datasets and the optimum colours. Test results show that the CAT02 with the new matrix predicted corresponding colours without negative TSVs for all optimum colours and the colour matching functions of the two CIE standard observers under the test illuminants considered. However, the accuracy with the new matrix for predicting the visual data is approximately 1 CIELAB colour difference unit worse compared with the original CAT02. This indicates that accuracy has to be sacrificed to achieve the non‐negativity constraint for the TSVs of the corresponding colours. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2011     

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     

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.