Color space of the coloroid color system

The Coloroid color system is a Hungarian standard color order system. This article describes the color space of the Coloroid system and its relationship to the CIE colorimetric space and the spaces associated with the Munsell and DIN color order systems. The Coloroid system is presented as a compromise of principles of uniformity in regard to color difference and color harmony, as well as ease of mapping into the CIE colorimetric space.     

Hue uniformity and the CIELAB space and color difference formula

The hue uniformity of the CIELAB system is investigated using a hue circle of Munsell colors at value 6 and chroma 14 and experimentally determined hue coefficient data. CIELAB hue differences for equal Munsell hue increments are found to vary up to nearly a factor 4, and hue coefficients differ from the experimentally determined ones by up to 40% at certain wavelengths. Dominant wavelengths assigned by the CIELAB system to individual Munsell hues are found to vary up to 35 nm from those of the Munsell Renotations. Four other color space systems are compared with widely differing but comparable results. The CIE 2° color-matching functions are adapted to result in a set of opponent-color functions accurately representing the Munsell Hue and Chroma data. A call is made for the experimental determination of the “standard hue observer” as a step toward an improved color space/color-difference formula. © 1998 John Wiley & Sons, Inc. Col Res Appl, 23, 314–322, 1998     

Correlations between color attributes and children's color preferences

This study examined the role of color attributes (lightness and saturation) on children's color preferences for interior room colors. It also investigated children's most preferred colors among each of the five major hue families in the Munsell color system using scale‐models. Previous color preference studies have typically been done with small color chips or papers, which are very different from seeing a color applied on wall surfaces. A simulation method allowed for investigating the value of color in real contexts and controlling confounding variables. Forty‐five color samples were displayed on scale‐models to 63 children ages 7–11 years old. This study identified children's most preferred colors among each of the five major hue families in Munsell color system. It also demonstrated that saturation was positively correlated with children's preferences in the red, green, blue, and purple hue families. In the yellow hue family, interestingly, lightness has a positive correlation with preferences. Children's gender differences were found in that girls prefer red and purple more than boys. These findings lead to color application guidelines for designers to understand better color and eventually to create improved environments for children and their families. © 2013 Wiley Periodicals, Inc. Col Res Appl, 39, 452–462, 2014     

Geodesic calculation of color difference formulas and comparison with the munsell color order system

Riemannian metric tensors of color difference formulas are derived from the line elements in a color space. The shortest curve between two points in a color space can be calculated from the metric tensors. This shortest curve is called a geodesic. In this article, the authors present computed geodesic curves and corresponding contours of the CIELAB ( ), the CIELUV ( ), the OSA‐UCS (ΔE_E) and an infinitesimal approximation of the CIEDE2000 (ΔE₀₀) color difference metrics in the CIELAB color space. At a fixed value of lightness L*, geodesic curves originating from the achromatic point and their corresponding contours of the above four formulas in the CIELAB color space can be described as hue geodesics and chroma contours. The Munsell chromas and hue circles at the Munsell values 3, 5, and 7 are compared with computed hue geodesics and chroma contours of these formulas at three different fixed lightness values. It is found that the Munsell chromas and hue circles do not the match the computed hue geodesics and chroma contours of above mentioned formulas at different Munsell values. The results also show that the distribution of color stimuli predicted by the infinitesimal approximation of CIEDE2000 (ΔE₀₀) and the OSA‐UCS (ΔE_E) in the CIELAB color space are in general not better than the conventional CIELAB (ΔE) and CIELUV (ΔE) formulas. © 2012 Wiley Periodicals, Inc. Col Res Appl, 38, 259–266, 2013     

Prediction of color appearance under various adapting conditions

A model of color vision is given to predict color appearance of object colors under various illuminants and illuminance levels. The model constitutes a uniform color-appearance space under any adapting condition, and can predict the metric quantities relating to the following color perceptions: (1) constant-hue loci, (2) the Munsell color scheme, (3) the increase of brightness contrast of nonselective samples with increasing adapting-illuminance level, (4) the Helson-Judd effect, and (5) the increase of colorfulness of chromatic samples with increasing adapting-illuminance level.     

A residual modified transformation formula from munsell to sRGB color system

A residual modified transformation formula from Munsell to sRGB color system is presented in this article. The development of the transformation formula is based on the 1625 Munsell color chips in the Munsell Renotation Data that could be displayed on the sRGB monitor. The developed transformation formula consists of two models, one is named as the corresponding matrix model and the other is the residual modified model. The corresponding matrix model was obtained using numerical analysis methods to map each chip color attribute values from Munsell to sRGB and then its corresponding matrix for each Hue was constructed. The residual modified model was obtained using the discrete cosine transform to construct a residual modified function, which was used to modify the transformation error of each chip after applying the corresponding matrix model. The transformed accuracy rate for the corresponding matrix model is 88.4% and for the residual modified model can be enhanced to 96.6% for all of the chips. The developed transformation formula can be applied to research in which Munsell colors are presented on the sRGB monitor. With the aid of these formulas, designers can show the advanced real‐time results on a sRGB monitor for the product's color planning based on Munsell color system. Therefore, this research has a great contribution on the practical application for color planning in product design. © 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 243–255, 2015     

Spectral spaces and color spaces

It has long been known that color experiences under controlled conditions may be ordered into a color space based on three primary attributes. It is also known that the color of an object depends on its spectral reflectance function, among other factors. Using dimensionality reduction techniques applied to reflectance measurements (in our case a published set of 1 nm interval reflectance functions of Munsell color chips) it is possible to construct 3D spaces of various kinds. In this article we compare color spaces, perceptual or based on dimensionality reduction using color matching functions and additional operations (uniform color space), to spectral spaces derived with a variety of dimensionality reduction techniques. Most spectral spaces put object spectra into the ordinal order of a psychological color space, but so do many random continuous functions. In terms of interval scales there are large differences between color and spectral spaces. In spectral spaces psychophysical metamers are located in different places. © 2003 Wiley Periodicals, Inc. Col Res Appl, 29, 29–37, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10211     

Comparison of color vision models based on spectral color representation

Recent break‐throughs in retinal imaging have raised new questions for color vision research, and the existing color vision models should be re‐evaluated. Many color vision models are based on an assumption that there are no differences in the detection phase, neither in the spatial configuration nor in the spectral sensitivities of cells. In this article, we have run experiments with four different color vision models. This evaluation gives us more knowledge about the essential properties of the models. We show how the tested color vision models are able to replicate the behaviour of human color vision by evaluating their performance in Farnsworth‐Munsell 100‐Hue color vision test. Also, the wavelength discrimination power of each model is presented and the properties of color spaces spanned by models are examined using samples from Munsell Book of Color. Our experiments show that there are large differences in the properties of different models. © 2009 Wiley Periodicals, Inc. Col Res Appl, 34, 341–350, 2009     

Survey of color order systems

Important modern color order systems accompanied by physical exemplifications (atlases) are surveyed; one of great historical interest, though not currently available, is included. The systems covered include the Munsell, Natural Color, OSA-UCS, DIN, Coloroid, and Ostwald systems. Their history, guiding principles, variables, and relation to the CIE system are described. Some of the interrelationships among the systems are then considered, specifically those between the Munsell system and the Natural Color and OSA-UCS systems. Implications for the consideration of international standard color order systems are mentioned.     

Atdn: Toward a uniform color space

To derive a uniform chromaticity space for small color differences, we applied compressive intensity-response functions of the form ρ = Iⁿ/(σ + Iⁿ) to each of the four color signals from the T (red vs. green) and D (blue vs. yellow) mechanisms of the ATD vector model for color vision. The values of σ and n for each response were optimized by computer iteration to provide reasonably uniform color spaces (ATDN) for describing the color-discrimination data of MacAdam [J. Opt. Soc. Am. 32 , 246-274 (1942)] and Pointer [J. Opt. Soc. Am. 64 , 750–759 (1974)]. To determine how well ATDN accounts for large color differences, we transformed the coordinates of the Munsell renotation system to ATDN space. Origin-bound radial lines and origin-centered circles in ATDN are about equivalent to those of CIELAB in approximating iso-hue and iso-sat-uration contours of the Munsell system. A computer program written in BASIC that can be used to transform 1931 CIE X, Y, Z values to points in ATDN space is included as an appendix.     

Judd's contributions to color metrics and evaluation of color differences

The contributions of Dr. Deane Brewster Judd to colorimetry extended over five decades. Among the most crucial contributions to the development of modern colorimetry were his studies of colorimetric purity, relations among color-mixture and luminosity data, visual sensibility to color differences, uniform chromaticity diagrams, Munsell notation and renotation, color names, color blindness and anomalies, color-vision theory, and uniform color scales.     

Computational tongue color simulation in tongue diagnosis

Tongue color is one of the important indices for tongue diagnosis in traditional Chinese medicine. This study aims to analyze tongue colors of computational tongue diagnosis in traditional Chinese medicine using scientific quantification and computational simulation. The tongue color data are established according to the experiment in which the doctors who use Chinese traditional medicine assessed standard Munsell color charts under the standard lighting environment. Tongue color is classified into six color names, which are pale red, light red, red, crimson, dark red, and purple. The doctors assessed Munsell color charts to find the corresponding color charts' distributions of each color name in tongue color. The hue-lightness-chroma data of the chosen Munsell color charts were transformed to CIE xyY using the look-up table computation, then further were converted to CIELAB values and sRGB data. Based on the 95% confidence ellipses formed on CIELAB (a^*, b^*) plane and CIELAB (C^*, L^*) plane, the comparisons between tongue colors and general colors were analyzed. The computational tongue image simulation combining the elements of color, texture, and moisture was successfully established. This computational simulation method could potentially become a useful tool for teaching and learning diagnoses in the education of Chinese medicine.     

Surface color and color constancy

Color constancy is often treated as the tendency of surfaces to stay the same perceived color under changing illumination or context (removing/adding/replacing surrounding objects). But these types of color constancies are not basic ones and there is another kind of color constancy that is fundamental for the explanation of all color constancy phenomena. We experience it when looking at a curved uniformly colored surface or when changing the shape of the surface. A new concept of surface color is developed and the variety of all perceived colors is suggested to be described as a nine-dimensional set of 3 X 3 matrices corresponding to different surface colors. Examples of color matrices calculated for some colored surfaces being viewed by the standard viewer are presented and arguments supporting the concept are discussed. It is shown that the set of color matrices represents all perceived colors quite adequately.     

A comparison of five color order systems

Five color order systems (Munsell Renotations, Munsell Re‐renotations, OSA‐UCS, NCS, and Colorcurve) have been compared by optimizing the powers applied to individual opponent‐color functions. The results indicate general similarities in that powers applied to the red and green functions tend to be closer to 1, while those applied to the blue function and the yellow function are generally smaller. Specifically, there are many individual differences that make each system unique. The results inspire confidence in the veracity of the opponent‐color system methodology. © 2000 John Wiley & Sons, Inc. Col Res Appl, 25, 123–131, 2000     

Centroids of color categories compared by two methods

A procedure is described whereby the subset of Munsell colors of maximum chroma, which has been used by anthropologists to study color naming since Berlin and Kay in 1969, can be specified in the L,j,g coordinate system developed more recently by the Uniform Color Scales Committee of the Optical Society of America. The latter permits a meaningful specification of the centroid location of colors named by each basic term. The procedure is validated by comparing centroids obtained from six subjects who named samples of both the Munsell and OSA sets, and its usefulness is illustrated by comparing data from a four-year old who named only OSA samples and four- and two-year-olds who named only Munsell colors.     

Visual and photographic assessment of wine color

This article presents a color chart explicitly designed for the visual color assessment of wines as a part of more comprehensive hedonistic or analytical tasting systems. The chart is based on visual, colorimetric, and in situ evaluations of existent wine color and the techniques for its assessment in wine sensory evaluation. The system is specified in Munsell coordinates and corresponding sRGB values. Its derivation and use is described and a photographic system for measurement-based implementation of the system is introduced.     

Describing natural colors with Munsell and NCS color systems

The Munsell Color System and the Natural Color System are widely used but they have some limitations due to the manufacturing process and sampling choices. To estimate quantitatively these limitations we compared the colors of natural scenes with the colors represented by these systems under a wide range of illuminants. Spectral data from the two systems and from natural scenes were used in the analysis. It was found that a considerable portion of natural colors are not accounted by these systems, mainly colors with low lightness levels. Under D65 the Munsell Color System color volume corresponds to 72% of the Natural Color System color volume which in turn represents only 53% of the natural scenes color volume. If individual colors are considered, less than half are contained within these systems. To obtain a complete match to the natural colors contained by the color systems thresholds of 7 and 5 CIELAB units would be required for Munsell Color System and Natural Color System, respectively. Variations with the illuminant are generally modest showing that both system work similarly across different illuminations. Although these Color Systems have limitations in describing low lightness colors they perform quite well for medium to high levels of lightness.     

Optimization of color reproduction on CRT‐color monitors

In the present experimental study, we quantify the influence of the brightness and contrast levels of a CRT‐color monitor in the color reproduction of 60 Munsell chips distributed throughout the chromatic diagram. The images were captured by two CCD cameras, and the color differences were evaluated after reproducing the chips on a color monitor (the experiment was performed with 3 different monitors) for 9 combinations of brightness‐contrast levels. We evaluated the color differences with 3 different formulas: CIELAB, CIELUV, and CIE94. The results indicate that the optimal settings of a monitor, to minimize the color differences, is a medium or minimum brightness level in combination with a maximum contrast level. This combination ensures a more faithful color reproduction with respect to the original image. © 1999 John Wiley & Sons, Inc. Col Res Appl, 24, 207–213, 1999