An adaptive approach to create on‐demand color schemes for mapping quantitative geographic data

Creating a satisfying quantitative color scheme is challenging for both novices and experts. Geovisualization often suffers from the misuse and misunderstanding of quantitative color schemes. This article presents an adaptive method to create ready‐to‐use quantitative schemes. A probability‐based method for color selection is presented to quantify the selection of quantitative colors from learning samples of varying popularity. To shape the color transitions, a regression analysis is performed to fit the mathematical curves for the transitions of hue, saturation, and brightness. Finally, the problem of creating satisfying quantitative schemes is translated into a multiconstraint optimization problem. A discretize‐and‐filter method is also presented to solve the optimization problem of globally identifying a suitable scheme in a continuous color space. The proposed method is evaluated with a case study, and the results indicate that the proposed method can derive satisfying schemes. In addition, the proposed method is adaptive to mapping feature, target reader and target device.     

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.     

A User‐Oriented Method for Preferential Color Scheme Generation

Harmony and preference are two important factors in constructing color combination for the purpose of color design. We presented a method for generating harmonious color scheme in a previous project. As an extension to the project, we propose here a method for generating color schemes that are based on user's preference. We considered color combinations as a set of color relations rather than a summation of specific color components (color elements); and we derived a model of six‐variable color relations, representative value of hue, representative value of saturation, representative value of lightness, span of hue, span of saturation, and span of lightness. With this model, color combinations can be expressed as specific parameters of the six‐variable model. Individual preferences are represented as certain parameters, from which new color schemes can be reconstructed to meet individual requirements. An interactive system for generating preferential color schemes is built with all these principles integrated. As a color design toolkit for user study, the system accesses user's preference features for color combinations, and provides new color schemes that fit the user's need. User study shows that both professionals and novices can generally acquire preferential color schemes of their own. © 2013 Wiley Periodicals, Inc. Col Res Appl, 40, 147–156, 2015     

An intelligent skin‐color capture method based on fuzzy C‐means with applications

Consumer behavior is complicated. In the cosmetic market, personal intuition and fashion trends for color selection are guidelines for consumers. A systematic method for female facial skin‐color classification and an application in the makeup market are proposed in this study. In this article, face recognition with a large number of images is first discussed. Then, an innovative method to capture color at selected points is presented and complexion‐aggregated analysis is performed. This innovative method is an extension of face‐recognition theory. Images in RGB format are converted to CIELAB format during data collection and then Fuzzy C‐means theory is used to cluster and group the data. The results are classified and grouped in Lab value and RGB index. Two programs are created. The first program, “FaceRGB,” captures color automatically from images. The second program, “ColorFCM,” clusters and groups the skin‐color information. The results can be used to assist an expert system in the selection of customized colors during makeup and new‐product development.     

A harmony-based approach to generating sequential color schemes for maps

Generating high-quality sequential color schemes for maps is challenging for most mapmakers. This article presents a harmony-based approach for automatically generating sequential color schemes for maps. The proposed approach consists of two steps: (a) color harmony quantification for sequential color schemes on maps and (b) color scheme generation using quantified color harmony factors. The approach was tested using three experimental maps, including the Chinese water body density index map, Chinese vegetation cover index map, and Chinese population density map. Effectiveness was evaluated by comparing color schemes generated by the proposed approach with those created by the probability-based method and ColorBrewer. Twenty-six participants were invited to rate each map color scheme using a 5-point scale. A t test was also used to examine the significance of the difference. The results show that the mean points of color schemes using the proposed approach are higher than those using the probability-based method, and the corresponding P-values are far lower than .05, which suggests that the proposed approach is better than the probability-based method and can improve the sequential color scheme quality in automatic ways. The mean points of color schemes created using the proposed approach are also slightly higher than or similar to those of ColorBrewer, which are well-known map color schemes manually designed by an experienced cartographer. This result further suggests that the proposed approach can meet the requirement of automatic generation for high-quality sequential color schemes on maps.     

Automatic detection of layout of color yarns of yarn‐dyed fabric. Part 3: Double‐system‐Mélange color fabrics

Automat layout detection of color yarns is necessary for weaving and producing processes of yarn‐dyed fabrics. This study presents a novel approach to inspect the layout of color yarns of double‐system‐mélange color fabrics automatically, which is Part III of the series of studies to develop a computer vision‐based system for automatic inspection of color yarn layout for yarn‐dyed fabrics. The inspection of single‐system‐mélange color fabrics has been realized in Part I of the series of studies. Integrating the projection‐based region segmentation method proposed in Part I and the FCM‐based stepwise classification method proposed in Part II, the proposed approach is composed of three steps: (1) fabric region segmentation, (2) fabric region selection, and (3) layout of color yarns recognition. In the first step, the fabric regions are segmented by the projection‐based region segmentation method. In the second step, the reasonable fabric regions are selected by analyzing their color histograms and comparing their weft color's frequency. In the third step, the layout of color yarn is recognized by the FCM‐based stepwise classification method, and the precise layouts of color warps and wefts are produced. The experimental analysis proved that the proposed method can recognize the layout of color yarns of double‐system‐mélange color fabrics correctly by testing four different color fabrics and three pieces of same yarn‐dyed fabrics. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 250–260, 2017     

Color selection in the consideration of color harmony for interior design

A color selection method that considers subjective principles is becoming more and more necessary in a computer‐based color management system. However, one from an engineering perspective has received limited attention. Previously, we developed an approach to measure the degree of color harmony by the similarity of a pleasure‐related function, CLD (color linguistic distribution), to a RHD (reference harmony distribution) on a one‐dimensional image scale of EXCITING–CALM. Following this approach, a new color selection system is presented in this article by modulating the CLD on the image scale. The procedure used is to encode an inharmonious image as a CLD, then it is modulated and referred to as a RHD, called an imagery specification. Finally, the specified CLD is decoded and reconstructed as a harmonious image in an operated color space. Four types of RHD are compared: three ideal fuzzy sets scaled to extremely calm, quite calm, and slightly calm, and the practical one measured from social trends. For verification, the harmony grade of the decoded image can be measured based on the referred RHD. As a result, four times the harmonic degree of the decoded image is gained than the originally encoded one. For application purposes, the proposed system is suitable for applications related to human subjectivity. © 2000 John Wiley & Sons, Inc. Col Res Appl, 25, 20–31, 2000     

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     

Color‐emotion associations,designing color schemes for urban environment‐architectural settings

Color in urban design has become an important issue, each city may present different colors which help to define and describe its architectural features. In the study, color in urban design with architectural setting is studied, façade colors are analyzed with a specific emphasis on the following research questions; “Can color schemes be designed in respect to color‐emotion associations? ” and “Are color‐emotion associations affective while designing architectural setting‐urban environment?.” Non‐color experts, 170 people, from different European and non‐European countries were asked to match the most appropriate adjectives with the given street views in accordance to their color schemes. In the first step, the effect of color is identified in relation to architectural environment‐urban setting, second the relative effect of color is studied as a component of the material. A categorical specification on color cognition and linguistic level of representation is attempted. The results can be a starting point to highlight the importance of preparing color schemes in regard to color‐emotion associations. Abstract color schemes may also provide us an idea about image setting, especially at design process stage. In the study, keywords are linked as environment‐response pairs; such as quiet, calming, lively, exclusive, reserved, and natural. Human psychophysical structure such as “warm‐cool,” “heavy‐light” in regard to visualizing certain colors are evaluated and described in terms of building materials.     

Transferring the color imagery from an image: A color network model for assisting color combination

In order to transfer the color imagery from an image to another object to generate color schemes, a color network model is proposed. It consists of two subnets: source net for describing the color information of the reference image; target net for demonstrating the target object to be colored. Thus, the problem of reusing features of color patterns is translated into the mapping process from the source net to target net. Four indicators are designed to measure the conformity between the two nets: color sequence, adjacency, concentration, and the subspace size. In the meantime, a comprehensive aesthetic evaluation given by the designer is introduced to search the optimum combination of the four indicators to help generate imagery matching schemes. A prototype system is developed based on CorelDraw as a design tool. The feasibility of the color network model is then verified through a color combination of graphic design task.     

Color space and its divisions

A synthesis of the author's recent work on color‐order systems and color‐difference evaluation is provided in context of current knowledge and practices. The development of a colorimetric model is demonstrated using Munsell “Celtic crosses” as a model of perceptual space. Issues surrounding color‐matching functions, unique hues, the Helmholtz–Kohlrausch effect, and lightness and chroma crispening are addressed, as is the difficulty of reconciling a difference‐based hue, chroma, lightness model with an Euclidean model. A new lightness scale and treatment of lightness crispening is proposed. The results indicate that, despite problems, relatively simple modified opponent‐color models provide good accuracy in predicting color‐order system and supra‐threshold small color‐difference data. © 2001 John Wiley & Sons, Inc. Col Res Appl, 26, 209–222, 2001     

An interactive method for generating harmonious color schemes

We present an interactive visualization tool for generating color schemes that can be used by both professional artists and novice designers to improve their design efficiency. The method is developed on two color harmony principles of familial factors and rhythmic spans from conventional color theories. The interactive tool makes use of these principles for users to interactively generate colors palettes containing harmonious combinations in the hue, saturation, and lightness color space in as few steps as possible. A pilot study with 20 participants has shown that this tool provides efficient workflow, color‐scheme harmony, and intuitive interaction, demonstrating the usefulness of the method. This work contributes to an artistic‐theory driven harmonious color‐scheme generation and to interactive user interfaces visualizing color relationships. © 2012 Wiley Periodicals, Inc. Col Res Appl, 39, 70–78, 2014     

Proposal for selecting two‐color combinations with various affections. Part I: Introduction of the method

A method is proposed for selecting two‐color combinations with various feelings. Feelings used are pleasantness, contrast, floridness, warmth, and their combinations. The proposed method is given by its flow chart for selecting the candidates of two‐color combinations adapting to target feeling(s). The effectiveness of the proposed method is shown by the correlation coefficients between observed and predicted values for four kinds of feelings. Munsell H V/Cs of each component color are necessary for prediction; the prediction formulas are given for estimating the degree of each feeling for any two‐color combinations. The proposed method can be expanded to three‐color combinations. This proposal is expected to assist color designers, who can choose their usable color combinations from the candidates selected by the proposed method. © 2009 Wiley Periodicals, Inc. Col Res Appl, 34, 128–134, 2009     

Use of gray system theory in product‐color planning

A quantitative evaluation method for the CIE color‐planning activity within the product design cycle is proposed in this article. The questionnaire‐based process that is traditionally employed to obtain objective color psychology tends to be time‐consuming. Accordingly, this study proposes the use of gray system theory to overcome this problem. In the CIE color system, colors are defined by three primary colors, R (red), G (green), and B (blue). Using these three principal hues with fixed equigap sequences to simulate specific basic color samples is an efficient means of investigating unicolor images on a personal computer. However, a gray relational generating operation can be used to simulate colors beyond these basic samples and to predict the corresponding membership values for semantic words. In addition, the gray clustering operation is introduced to predict the overall color image evaluation of multicolored products. The predicted evaluation results of the gray system theory and a back‐propagation neural network are both compared with experimentally verified results. The results indicate that the gray forecasting model is the more effective means of predicting the image evaluation, and therefore, the method is adopted within the color‐planning activity. Although this study takes the example of the Internet‐aided color planning of a baby walker as a case study, the proposed method can also be used on other products. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 222–231, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20009     

Pattern‐driven color pattern recognition for printed fabric motif design

Pattern‐driven design method is an important data‐driven design method for printed fabric motif design in textiles and clothing industry. We introduce a novel framework for automatic design of color patterns in real‐world fabric motif images. The novelty of our work is to formulate the recognition of an underlying color pattern element as a spatial, multi‐target tracking, classification, segmentation and similarity association process using a new and efficient color feature encoding method. The proposed design method is based on pattern‐driven color pattern recognition and indexing from the element image database. A series of color pattern recognition algorithms are used for color and pattern feature extraction. The local statistical corner features and Markov random field model are used for motif unit tiling detection and conversion. The color feature encoding problem is modeled in a gray‐scale color difference optimization problem, which can be solved quickly by existing algorithms. Color pattern feature matching, segmentation and indexing techniques are then used to locate and replace the elements in the motif unit image with similar elements in the database. Experiments show that the approach proposed in this study is effective for color pattern recognition and printed fabric motif design.     

A methodology for predicting the color trend to get a three‐colored combination

A color design/selection system for predicting the color trend based on aesthetic measures is proposed in this article. In this method, the analytic hierarchy process theory was used to evaluate the weights for four major consumption style factors in human environment, including Economy, Education, Culture, and Technology. Then 10 product imageries were selected by using the questionnaire, and mapped the images and the factors with the weighted results and clustered both variables with the corresponding ranks. During the implementation procedure, 111 colors samples covering the entire domain of the PCCS (Practical Color Co‐ordinate System) color system were taken, and the aesthetic measure for three‐colored harmony based on aesthetic measure theory was calculated. Then 200 tri‐colored combinations were divided into 10 clusters by using fuzzy clustering. The three‐colored products were then mapped into each cluster with the calculated grand average and Standard Deviation of the imagery values obtained for the three‐colored products. According to the above implementation logic, the relationship among the consumption style factors, the images, as well as the tri‐colored cars can be obtained, and then used to construct a color trend based on market requirement. With the aid of this system, one can get a three‐colored car to match his/her requirement. Although the selection of three‐colored car is taken as an example to specify the methodology, it can also be used to develop a system for other products. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 102–114, 2017     

A study of color conspicuity for ease‐of‐use inference in visualization

Novice designers of visualizations need support to find easy‐to‐use color schemes for visualizations. This article introduces a method of conspicuity inference for a color selection support system that is applicable to a wide variety of visualizations. In previous research, data on color conspicuity by computer GUI interface were collected by having subjects adjust the relative sizes of two figures on a ground in order to find conspicuity balance. This article outlines a new conspicuity inference system, which uses a neural network to produce a color conspicuity value from the system RGB values of two figures and a potential ground. The output value is the ideal relative area of the two figures. This value is applied to visualization designs by weighting each conspicuity value with a ground coefficient, the relative size of every color in a design. Color selection and evaluation experiments show a significant relationship of conspicuity balance, as inferred by this system, for subjective ease‐of‐use evaluation scores for 200 novice designs. Topics for future research include developing the system's characteristically simple parameters within the limited scope and integrating conspicuity balance with other factors such as visibility, discriminability, and color harmony. © 2002 Wiley Periodicals, Inc. Col Res Appl, 27, 74–82, 2002; DOI 10.1002/col.10033     

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     

Michromatic scope for enhancement of color difference

A michromatic (microscope plus chromatic) scope is a device that enhances the color discrimination between two spectral color datasets. Three spectral filters are required, instead of the conventional red, green, and blue filters, for the implementation of a michromatic camera. In this study, we describe two approaches to the design of these filters: in the first case, the design is based on the direct optimization of the filter characteristics (transmittance), whereas in the second case, the design is based on the nonnegative tensor factorization (NTF) of the spectral datasets. A michromatic camera can be implemented using these filters along with compatible postprocessing in‐camera firmware. Here, we performed experiments with two color datasets: one comprising skin and vein colors, and one comprising skin and cosmetics colors. These were further divided into a training set and a test set. The filters were defined using the training set, and the operation of the filters was tested and magnified using the test set. Our experiments demonstrated that the proposed approaches are suitable for color discrimination. For the first color dataset, the enhancement produced using the optimized filters was up to 252% of the original value, and the average color difference ΔE was increased from 2.82 to 9.93. NTF and preprocessing further enhanced the ΔE up to 21.84. For the second color dataset, NTF and postprocessing enhanced the ΔE from 4.33 to 29.19. The proposed discrimination enhancement could be physically implemented in a designated digital charge‐coupled device camera with proper filter installation and compatible postprocessing. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2010