A systematic approach of predicting color preference on the basis of gray relational grade

During the color design process, it is critical to create diversified color schemes for various consumer groups. It is also important to allow members in a design team to brainstorm for creative ideas. A theory of inspecting natural color elements was proposed in this study based on the CIE 1976 (L*,a*,b*) (CIE 1976) color space and the fuzzy c‐means clustering method. A calculation model was built to determine people's preference for colors based on a serialized system. To determine which factors affect the prediction of consumers' preference for a series of products, a gray relational color preference system was used in combination with gray relational grade so that a designer can obtain reasonable prediction results. The proposed system recommends not only the optimal colors for a product but also the optimal color scheme for a series of products.     

Gray and grayness—its complexities in color appearance of surface colors

Complexities on the roles of reference color gray and grayness are reviewed. They are essential in color appearance, but gray is an implicit color. Although “grayness” is not explicitly used in visual color assessment of surface colors or color order systems, gray can be combined with any colors having six primary‐color components using the term “grayish,” for example, grayish red and grayish yellow. However, the existing region of grayness is limited in a part of color‐appearance space. Illuminance dependency of gray perception is also clarified. Existence of two kinds of psychometric quantities are suggested: one is the attribute of grayness based on its psychological amount in a grayish color under study, and the other is the attribute of brightness of the grayish color under a specified illuminance, psychophysical quantity. The Nayatani‐Theoretical color order system, which uses three opponent‐colors axes, can clarify the above complexities of gray and grayness. Its importance is the same as six primary colors, red–green, yellow–blue, and white–black. © 2012 Wiley Periodicals, Inc. Col Res Appl, 39, 37–44, 2014     

Measuring linear density of threads in single‐system‐mélange color fabrics with FCM algorithm

According to the color yarns in the fabric, the fabrics can be divided into three categories: solid color fabrics, single‐system‐mélange color fabrics, and double‐system‐mélange color fabrics. The density of solid fabrics can be inspected with gray‐projection method or Fourier analysis method. But the methods cannot be applied to yarn‐dyed fabrics directly. A method for detecting the density of single‐system‐mélange color fabrics will be discussed in this article. By analyzing the pattern and color characters of single‐system‐mélange color fabrics, fuzzy C‐means algorithm is proposed to classify the colors in the fabric image based on CIELAB color space first. With the color segmentation results, the fabric can be divided into different blocks. The yarns can be located in different blocks with different average gray‐levels, and then the number of yarns can be counted in each block. The linear density of threads can be obtained by counting the yarns in a unit length finally. The experiment proved that the algorithm proposed in this study can inspect the density of single‐system‐mélange color fabric successfully. © 2012 Wiley Periodicals, Inc. Col Res Appl, 38, 456–462, 2013     

Visual evaluation at scale of threshold to suprathreshold color difference

Visual evaluation experiments of color discrimination threshold and suprathreshold color‐difference comparison were carried out using CRT colors based on the psychophysical methods of interleaved staircase and constant stimuli, respectively. A large set of experimental data was generated ranged from threshold to large suprathreshold color difference at the five CIE color centers. The visual data were analyzed in detail for every observer at each visual scale to show the effect of color‐difference magnitude on the observer precision. The chromaticity ellipses from this study were compared with four previous published data, of CRT colors by Cui and Luo, and of surface colors by RIT‐DuPont, Cheung and Rigg, and Guan and Luo, to report the reproducibility of this kind of experiment using CRT colors and the variations between CRT and surface data, respectively. The present threshold data were also compared against the different suprathreshold data to show the effect of color‐difference scales. The visual results were further used to test the three advance color‐difference formulae, CMC, CIE94, and CIEDE2000, together with the basic CIELAB equation. In their original forms or with optimized K_L values, the CIEDE2000 outperformed others, followed by CMC, and with the CIELAB and CIE94 the poorest for predicting the combined dataset of all color centers in the present study. © 2005 Wiley Periodicals, Inc. Col Res Appl, 30, 198–208, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20106     

A quantitative network model for color categorization

To clarify the higher‐order mechanism of human color perception, we measured the color appearances of 78 colored lights by an elemental color‐scaling method and by a categorical color naming method. The colors covered nearly the entire CIE 1931 xy‐chromaticity diagram with three different surrounds. The results showed that firm basic color zones derived by categorical color naming can be mapped with no overlap in an opponent‐color response space. We propose a network model with a threshold selector, maximum selectors, and multiplication units with gain factors to generate the categorical color responses quantitatively from the elemental color responses. The model can predict the categorical color naming results in different surround conditions with no change of parameters. This suggests that a nonlinear color vision mechanism for color categorization exists between the primary visual cortex (V1) and the inferior temporal cortex (IT) in the human brain. © 2002 Wiley Periodicals, Inc. Col Res Appl, 27, 225–232, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10060     

A systematic method for color planning in product design

A quantitative approach for color planning in product design is addressed in this article. the color image that a product has is quantified by using the membership function of a fuzzy set. the color plan for designing an ice shaver is used as an example to show the procedure. the Hue and Tone System and the Color Image Scale are used to transform colors into images or images into colors. the composite operation for fuzzy sets is used to simulate a color projection technique to get the semantic equivalence of words and colors. A computer program is built to get the membership functions between the colors and image words. the membership functions are arranged by size and suggested to the designer to help make a decision on what color should be used. In this manner, the psychology of customers can easily be captured by the designer, consequently increasing the efficiency of the decision process. Though a simple product is taken as an example here, this systematic method can be used to design other more complicated products. In addition, the results can be used to investigate the color psychology.     

An adaptive color similarity function suitable for image segmentation and its numerical evaluation

In this article, we present an adaptive color similarity function defined in a modified hue‐saturation‐intensity color space, which can be used directly as a metric to obtain pixel‐wise segmentation of color images among other applications. The color information of every pixel is integrated as a unit by an adaptive similarity function thus avoiding color information scattering. As a direct application we present an efficient interactive, supervised color segmentation method with linear complexity respect to the number of pixels of the input image. The process has three steps: (1) Manual selection of few pixels in a sample of the color to be segmented. (2) Automatic generation of the so called color similarity image (CSI), which is a gray level image with all the gray level tonalities associated with the selected color. (3) Automatic threshold of the CSI to obtain the final segmentation. The proposed technique is direct, simple and computationally inexpensive. The evaluation of the efficiency of the color segmentation method is presented showing good performance in all cases of study. A comparative study is made between the behavior of the proposed method and two comparable segmentation techniques in color images using (1) the Euclidean metric of the a* and b* color channels rejecting L* and (2) a probabilistic approach on a* and b* in the CIE L*a*b* color space. Our testing system can be used either to explore the behavior of a similarity function (or metric) in different color spaces or to explore different metrics (or similarity functions) in the same color space. It was obtained from the results that the color parameters a* and b* are not independent of the luminance parameter L* as one might initially assume in the CIE L*a*b* color space. We show that our solution improves the quality of the proposed color segmentation technique and its quick result is significant with respect to other solutions found in the literature. The method also gives a good performance in low chromaticity, gray level and low contrast images. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 156–172, 2017     

Suggested optimum primaries and gamut in color imaging

Suggested optimal “primaries” and concomitant optimal gamut for any form of device or product whose output serves as input to the normal human visual system: TV‐like images, or images reflected from illuminated hardcopy. For those devices and products using additive coloration, three spectral primaries 450–530–610 nm, and their associated gamut, are suggested as goals. For those using subtractive coloration, three reflective components, of width perhaps 50–60 nm at half‐height and peaking at the same wavelengths, are suggested. Thus, in either case, the light from each pixel of the generated color image entering the pupil of the normal human observer is composed of a mixture of that observer's prime colors. “Prime colors” are defined as usual as (a) the wavelengths marking the peaks of the three spectral sensitivities of the (trichromatic) normal human visual system, and, thus, (b) those spectral lights to which the normal human visual system responds most strongly per watt of power content input to the pupil. Spectral sensitivities of the normal human visual system are carefully distinguished from those of the CIE Standard Observers. © 2000 John Wiley & Sons, Inc. Col Res Appl, 25, 148–150, 2000     

Color separation for colored fiber blends based on the fuzzy C‐means cluster

Colored fibers can be blended in a certain proportion to achieve a specific color. It is a very hard task for the colorist to find a good recipe to meet the final product without the aid of computer. In this article, a color separation method for the colored fiber blends is discussed to substitute for some manual work. The fuzzy C‐means cluster is a way to group the color in the colored fiber blends image. The distance index, which is a key factor during the fuzzy C‐means cluster process, is calculated in the RGB color space and the HSV color space with some transformation. The final experiment result proved that the colors of each pixel in the blends' image can be replaced by corresponding cluster center associating colors in the HSV color space, and the main texture as well as the main color information about the fibers in the image is preserved. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2012     

Applying image‐based color palette for achieving high image quality of displays

In the highly competitive display market, manufacturers continuously develop new technologies to improve the image quality of displays. However, color measurement and visual assessment are time‐consuming to production lines. A new method to measure and improve color quality of the displays automatically therefore, is urgently needed to the manufacturers. This article proposes a familiar color correction strategy to optimize the colors of different displays by means of creating an image‐based color palette which enables color correction for familiar objects (e.g., facial skin, blue sky, or green grass) in the multidisplay systems. To produce the image‐based color palette, the 8‐bit RGB value of each pixel in an image is transformed to L*d*n* (lightness/dominant color/nondominant color) color channels, and the dominant‐color regions in an image are subsequently extracted from the dominant color (d*) channel. The memory color data of familiar objects can be set in reference monitor in advance to determine the dominant color (d*) channel. Then a series of palette colors are generated around a displayed image. The color palette will be displayed as a target for two‐dimensional colorimeter shooting to obtain the measured color data. The familiar color correction model was established based on a first‐order polynomial regression to achieve a polynomial fit between the measured color data and the reference color data on the color palette. The proposed method provides a solution to correct familiar colors on a displayed image, and maintains the original color gamut and tone characteristic in the multidisplay systems simultaneously. It is possible to achieve the preferred intent of the displayed images by using the proposed familiar color correction method. © 2012 Wiley Periodicals, Inc. Col Res Appl, 39, 154–168, 2014     

Comparing observers

Color‐matchingfunctions may be considered dimension reduction functions that project a spectral reflectance function into the desired space of colors. Using a gray metameric pair with maximal spectral difference we compare the abilities of various human and other observers with regard to the transition wavelengths for that metameric pair. Transition wavelengths are shown to be a convenient tool for comparing and classifying observers regardless of the number of dimension reduction functions. Four human observers were identified as differing in a comparable manner from the CIE 2° standard observer. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 183–186, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20004     

Recognized visual space of illumination: A new account of center‐surround simultaneous color contrast

Appearances of an object color in a space are determined by a cortical representation of illuminant for a space or the recognized visual space of illumination (RVSI). The simultaneous color contrast phenomenon on a simple center‐surround configuration can be explained by RVSI. It is hypothesized that our visual system constructs an RVSI on the surround and then that RVSI determines color appearance of the center test. If this is correct, the color contrast can be quite strong when the surround is enlarged to be an enclosed space. To support the hypothesis, color appearance of a physical gray test was measured in a green surround of various sizes. Observers were asked to do elementary color naming in the first experiment. The results showed same tendency for all observers: once the surround was extended to walls, a ceiling, and a floor of a box, perceived chromaticness abruptly increased. In other words, three‐dimensional surround evoked strong simultaneous color contrast. In the second experiment the matching method was employed with the green and other three surround colors: red, blue, and yellow. The results were consistent with the first experiment. The well‐known color contrast is thought to be a weak version of this color change. It suggested that RVSI plays an important role in the well‐known color contrast demonstration on two‐dimensional planes. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 255–260, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20019     

Proposal of an opponent‐colors system based on color‐appearance and color‐vision studies

A new theoretical color order system is proposed on the basis of various studies on color appearance and color vision. It has three orthogonal opponent‐colors axes and an improved chromatic strength of each hue. The system has color attributes whiteness w, blackness bk, grayness gr, chroma C, and hue H. A method is given for determining Munsell notations of any colors on any equi‐hue planes in the system. A method is also given for determining grayness regions and grayness values on hue‐chroma planes in the system. It is concluded that colors with the same color attributes [w, gr, bk, C] but with different hues in the theoretical space have approximately the same perceived lightness, the same degree of vividness (“azayakasa” in Japanese), and also the same color tone. The tone concept, for example used in the Practical Color Coordinate System (PCCS), is clarified perceptually. The proposed system is a basic and latent color‐order system to PCCS. In addition, the concept of veiling grayness by a pure color with any hue is introduced. Further, relationships are clarified between generalized chroma c(gen) and grayness. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 135–150, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10234     

Preprocessing to CIECAM02 input color with chromatic background

A preprocessing to CIECAM02 input color for color appearance prediction was proposed. In this study, 8640 color appearance matching pairs (NCS color charts with red, green, yellow, and blue backgrounds in a light booth and their reproductions with gray background on a CRT screen) were obtained by psychophysical experiment using the simultaneous‐binocular technique. Because only the lightness of background is included in CIECAM02, a color inducing vector based on opponent‐colors theory was introduced to preprocess CIECAM02 inputs, so that CIECAM02 may predict the corresponding color of an input color with chromatic background as well. By data fitting, a color preprocessing formula describing a relationship between the color inducing vector and the NCS chromaticness was conducted. Furthermore, the formula's performance was tested and the results showed that it was good for implementing the color appearance prediction of input colors with different chromatic backgrounds.© 2006 Wiley Periodicals, Inc. Col Res Appl, 32, 40–46, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20287     

Quantitative evaluation of color harmony via linguistic-based image scale for interior design

In order to develop a computer-based color consultation system, a quantitative evaluation of color harmony for interior images is constructed by using a linguistic-based image scale. Conventionally, color harmony from any engineering perspective has received limited attention, because its successful evaluation requires the development of pleasure-related features. In this study, a new pleasure-related function of color linguistic distribution (CLD) is proposed to quantitatively represent the mental color impression of interior images upon a designed one-dimensional linguistic-based image scale of EXCITING-CALM. Supported by a database that includes fashion trends, the distribution state of CLD is capable of indicating the fashion trends in Taiwan. Also, on the image scale, the grade of color harmony can be measured by its CLD similarity to a reference harmony distribution (RHD). Evaluated results demonstrate that interior design is primarily dominated by (low) saturation and (high) brightness. Also, results based on CIE1976 L*a*b* and CIE1976 L*u*v* color spaces are observed to be better than those based on the hue-dominated method of Moon-Spencer theory in corresponding with human's linguistic similarity, questionnaire-based harmony evaluation, and social trends. Moreover, our solution percentage has been investigated as 72.3%, which is better than those of the Moon-Spencer theory and of the “Law of Inverse Ratios of Areas.” For application purposes, the proposed system is suitable to analyze the mental impression of products from the perspective of the customer. © 1996 John Wiley & Sons, Inc.     

Color assessment of granitic rocks and implications for their ornamental utilization

The purpose of this study is to evaluate the factors affecting the assessment of granite color, such as grain size and texture, and to propose a methodology for this task which would reduce the margin of error associated with this procedure. For this purpose, an evaluation was carried out on the color of several granites with different textures used in the dimensional stone industry to highlight the importance of the sample area, the number of measurements per sample and the aperture of the equipment. A colorimeter was used to measure the granite color according to the CIE‐L*a*b* and CIE‐L*C*_abh_ab systems, in both large slabs and small samples selected in a processing plant of ornamental granites. Granite color characteristics from large slabs had to be obtained with at least 60 shots due to the variation between different slabs. Therefore, several samples are needed for granite characterization. The color of gray granites does not vary significantly. Nevertheless, the more weathered granites show significant differences which are more evident in the b*‐parameter, or the yellow–blue component, which allow the use of the colorimeter for quality control. By doing so significant differences among the rock pieces used in a single building can be avoided. There were no significant differences found in the color parameters from distinct apertures. However, due to the heterogeneity of the granite the color is evaluated better with larger apertures. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2012     

Skin‐color correction method based on hue template mapping for wide color gamut liquid crystal display devices

The development of wide color gamut (WCG) liquid crystal display (LCD) plays an important role in the high‐quality television (TV) field. Nowadays, people want their TV or display devices to have the capability of showing vivid colors while keeping skin colors as natural as they remember. Therefore, it is necessary to develop color‐correction technologies for WCG LCD system. A new color‐correction method named “natural skin‐color mapping algorithm” (NSCMA) for WCG LCD is proposed in this study. It can solve the skin‐color contour problem in color‐corrected images with simple skin‐color detection. Its development is based on the concepts of performing color mapping between source hue colors and target hue colors on each hue page. The polynomial regression is also applied to calculate the color mapping conversion matrices. Two color mapping factors called template‐size factor and tone‐compression factor are designed in NSCMA. The template‐size factor is used to adjust target template sizes adequately. The tone‐compression factor is designed to control the degrees of image enhancement. For facial skin‐color pictures, the appropriate settings of template‐size factor and tone‐compression factor will get suitable color image rendering on the WCG LCD. It is demonstrated that the WCG LCD can be corrected to show vivid color pictures and keep facial skin colors as natural as possible when the proposed NSCMA is performed. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2011     

Color reproduction on varnished cardboard packaging by using lower ink coverages due to the gray component replacement image processing

Even in these challenging times, cardboard packaging industry is increasing its revenue with stable annual increase prediction, but customers are increasing demands on the packaging with respect to environmental protection, attractiveness, and branding. This article aims to determine the influence of image processing in terms of gray component replacement and overprint varnishing on the color reproduction on a cardboard packaging material. A test chart with tertiary colors was defined and modified by different gray component replacement levels. It was printed in accordance with ISO norm on coated and uncoated cardboard and finished by overprinting water based, offset, and UV varnish. The prepared samples were evaluated by measuring surface coverage, tone value increase (dot gain) of primary colors and calculating ΔE₀₀ of defined tertiary colors. The results showed that gray component replacement application reduces ink consumption. Higher gray component replacement applied results in lower ink surface coverage, but the decrease is also dependent on the image content. The TVI (dot gain) is significantly influenced only by applying UV varnish, resulting with higher TVI. The color differences of the tertiary colors showed that increased level of the gray component replacement applied did not cause significant color differences, even decreased color difference in some cases. Additionally, applying gray component replacement decreased color differences in “reddish” part of the gamut. This research proved that lowering the ink consumption due to the gray component replacement will not cause significant differences in the color reproduction. Furthermore, varnishing with commercial offset or water-based varnish will not cause higher deviations in color reproduction, but use of the UV varnish would.     

Physics‐based spectral sharpening through filter‐chart calibration

The spectral overlap of color‐sampling filters increases errors when using a diagonal matrix transform, for color correction and reduces color distinction. Spectral sharpening is a transformation of colors that was introduced to reduce color‐constancy errors when the colors are collected through spectrally overlapping filters. The earlier color‐constancy methods improved color precision when the illuminant color is changed, but they overlooked the color distinction. In this article, we introduce a new spectral sharpening technique that has a good compromise of color precision and distinction, based on real physical constraints. The spectral overlap is measured through observing a gray reference chart with a set of real and spectrally disjoint filters selected by the user. The new sharpening method enables to sharpen colors obtained by a sensor without knowing the camera response functions. Experiments with real images showed that the colors sharpened by the new method have good levels of color precision and distinction as well. The color‐constancy performance is compared with the data‐based sharpening method in terms of both precision and distinction. © 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 564–576, 2015