Product color emotional design considering color layout

Emotional experience and demand for product colors are important factors in users' decisions to buy and use a product. Therefore, accurately characterizing users' emotional responses of the product's color has become a significant consideration for product color design. However, a product color design problem exists in which it is challenging to accurately and efficiently position users' color image space because consumers have completely different image perceptions when encountering a large number of color schemes generated by different color spatial distributions. For this reason, this article proposes a product color emotional design method that considers the color layout. A table is built of an elemental composition for product color design, which contains color layout forms. This article also establishes a mapping model based on the semantic difference and back propagation neural network between the users' color image perceptions and the elements of the product's color design. The system recommends a color layout form that matches the users' emotional image goal through the k‐nearest neighbor algorithm, and then the form is initialized using a genetic algorithm. The system can realize the solution to the optimal product color scheme by optimizing and evaluating the population. Designers can make intuitive choices and decisions through the product color recommendation system. Through an example of color design for industrial vacuum cleaners, this article shows that the method has satisfactory feasibility and applicability for solving the problem of the optimization of product color design with color layout forms.     

Research on color optimization of tricolor product considering color harmony and users' emotion

There are few studies on the tricolor design optimization, and the influence of color-area ratio on users' emotion has been ignored. This article aims to achieve multiobjective optimization of tricolor product color design. Two modes of color-area ratio are put forward. Using the proposed method of generating tricolor schemes, 368 tricolor schemes of the representative baby carriage are designed. Through questionnaire survey, color images are screened, and combined with correlation analysis and factor analysis, five perceptual features of color design are determined as “Order,” “Excitement,” “Temperature,” “Color harmony,” and “Users' emotional preference.” From two perspectives of color information processing, radial basis function neural networks are used to construct two emotional evaluation models. By integrating the radial basis function neural networks and a genetic algorithm, this study achieves multiobjective optimization of tricolor product color design for two optimization objectives of color harmony and users' emotional preference. Verification results show that the optimization schemes are significantly better than other schemes. Due to similar product characteristics, children's electric car is utilized to verify the generalization capability of the optimization method proposed in this article. It has been demonstrated that the optimization schemes achieve higher scores than randomly selected color schemes and the actual subjective scores match with the predicted scores computed by the color optimization method.     

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.     

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.     

Determining key colors from a design perspective using dE-means color clustering

Designing a mood board is a creative tool designers often employ at the start of a new (interior) design project. The colors of a mood board represent important information about the envisioned interior designs. In this article, we focus on digital mood boards and we propose a novel method to determine the mood boards' key colors from a design perspective using dE-means color clustering. This proposed algorithm includes a fixed initialization to overcome the non-deterministic nature of traditional k-means, and a merging step to ensure all colors in the calculated palette are at least a dE-threshold apart. Quantitative and qualitative results demonstrate that the proposed algorithm outperforms existing methods in determining the key colors from a design perspective. Additionally, we introduce a novel method to visualize the calculated color palettes that takes into account the contribution of individual pixels to the construction of the calculated color palettes. Finally, we demonstrate how the proposed algorithm can be used to characterize color palettes for various design styles like modern, industrial and art deco.     

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     

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     

Color scheme adjustment by fuzzy constraint satisfaction for color vision deficiencies

Color schemes or color combinations are widely used in printed materials and their digital versions, including web pages. These schemes convey information and create aesthetic appeal. Consequently, graphic designers have to strike a balance between accessibility and aesthetics with the color schemes they select. However, certain color schemes make the represented information confusing when viewers have color vision deficiencies (CVDs), which may lead to decrease in discriminability between used colors. What we will call the color‐scheme‐recoloring problem is the difficulty of optimizing a color scheme so as to preserve its original design and yet be simultaneously discriminable for all viewers, with or without CVDs. To address the problem, we formulated it within a framework of a fuzzy constraint satisfaction problem, a technique of artificial intelligence, and developed a tool for graphic designers. By utilizing the practical color co‐ordinate system (PCCS), we introduce concepts used in the field of graphic design. This work combines pre‐publication recoloring techniques for CVD viewers with elements of artificial intelligence, psychophysics, and psychology. © 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 446–464, 2015     

Product color emotional design adaptive to product shape feature variation

When a user selects a product, he/she considers the emotional experience induced by the product color. However, when affected by product shape feature, the color image perception space of a user becomes more complex and dynamic. To address this problem, a product color emotional design method adaptive to product shape feature variation is proposed in this article. Based on psychological means, factor analysis and semantic differential methods are used to elucidate the mechanism for the formation of a color image perception space of a user influenced by product shape feature. Using support vector regression, a product color image evaluation model adaptive to product shape feature variation is constructed, and is then optimized via a genetic algorithm. A corresponding design system is constructed based on the method proposed in this article. A case study involving the design of a thermos for children is presented to demonstrate the operational procedure involved in the proposed method and to verify its performance. The results of the verification experiments confirm that the design scheme from system recommendation essentially meets the anticipated image target and assists the designer effectively. The method and system proposed in this study can generate a product color design scheme, which is unconstrained by shape feature and can satisfy user emotional preferences and needs, and have a certain applicability and practicability.     

Pattern retrieval of yarn-dyed plaid fabric based on modified interactive genetic algorithm

With the development of perceptual consumption, consumers sometimes cannot explicitly describe the purchase demands or only based on impression, like the color perception and aesthetic experience. Based on the consumer's expression, it is difficult to design a new fabric by repeated proofing to meet the consumer's demands. To retrieve the existing patterns incorporating human intuition and emotion, this study proposed a novel pattern retrieval method of yarn-dyed plaid fabric using modified interactive genetic algorithm. Each pattern was encoded based on the design elements and visual features were extracted to bridge the semantic gap between the designer and the consumer. Survival of the fittest and two special mutation operators, addition and deletion, were designed to increase the diversity of the generations. During the evolution, the generated patterns were replaced by the most similar patterns in the database based on visual features. Experimental results showed that the proposed scheme is feasible and effective to extract the consumer's preferences and retrieve satisfactory patterns, helping the factory obtain the process sheet to guide production and save labor and material resources.     

Multiemotional product color design using gray theory and nondominated sorting genetic algorithm-III

When users select products, they consider the emotional experience resulting from the color of the product. However, the emotional demands of users for product color are multidimensional and diverse. It is very important yet difficult to accurately grasp multiemotional image requirements and effectively convert them into design elements. Therefore, multiemotional product color design (MEPCD) has become a very important and challenging research topic. In this article, a novel MEPCD system using gray theory (GT) and nondominated sorting genetic algorithm-III (NSGA-III) is proposed to effectively solve the MEPCD problem. First, the image perception spaces of users, which exist in different emotional dimensions, were collected using factor analysis and the semantic differential technique. Then, GT was used to establish a multidimensional emotional product color image evaluation model. Finally, NSGA-III was used to optimize and design a multiemotional color scheme for a product. Furthermore, according to actual conditions, an MEPCD system was established based on the proposed method. The design case study shows that the method and design system proposed in this article have a certain range of applicability and can effectively improve the practicality of MEPCD.     

Method of urban color plan based on spatial configuration

The present Chinese urban color plan inclined to assume the way of Japanese, which is based on the theory of the Geography of Color founded by Lenclos. However, both my interview in 2004 and my urban color plan in 2006 show that the way of planning from color to color can hardly meet the requirement of the rapidly developing Chinese cities, and the authority should leave more creative space to the designers. Researching the color scheme of Kirchsteigfeld done by Werner Spillmann in 1994 was very enlightening. Findings of other researchers also helped me to set up a systematic planning method. Considering the complexity of color in urban space, the present way of planning simply by color combination is not sufficient. Spatial configuration is the core of color plan, and the authority should emphasize the color pivot and vision rank to encourage creativity in real design. This article discusses the systematic method of color planning when considering Chinese urban plan system, and with typological means. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2013     

Image color adjustment for harmony with a target color

Although a number of methods have been developed for image adjustment in various applications, very little work has been done in the context of visual design. In this regard, this article introduces a novel and practical context of image color adjustment and develops a method to adjust an image for harmony with a target color. The experiment with designers revealed that designers made significant changes in hue dimension, and preferred to promote color similarity between the image and the target color. Based on insights from designers, we proposed a method to achieve a harmonious combination of an image and a color element by increasing the hue similarity between them. The result of a user test revealed that our method is particularly useful for images with nonliving objects but less effective for images involving human skin, foods, and so on. It is expected that the practical context investigated in this study can promote a variety of related studies that satisfy the tangible needs of industries and academia.     

Visual customization: Diversity in color preferences in the automotive interior and implications for interior design

Evolving multimodal mobility needs influences established human–product relationships and requires a deeper insight into color preferences for car interiors. Hence, a study was conducted in which 204 members of a web contest created 1,265 designs. After a peer‐evaluation process, 53 most‐appreciated and 34 least‐preferred interior color compositions were identified and compared to identify patterns in color choices. Besides, visual lightweight design by layering of large interior components such as the seat, a modest use of color and patterns accompanied by repetition and the framing of the entire interior to create a feeling of spaciousness were found. Additionally, differences in the type of color between most and least favored color designs were found. Brown and beige occur more frequently among the top‐ than the worst‐rated designs. Larger surfaces are favored in lighter hues and smaller components in darker hues.     

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.     

A spectrophotometric color matching algorithm for precolored fiber blends

In this article, a spectrophotometric color matching algorithm based on Stearns‐Noechel model is proposed. This algorithm was run to predict recipes for 48 viscose blends. Color differences between the original blend samples and the calculated were expressed in CIELAB units (10°standard observer). M (the empirical constant in Stearns‐Noechel model) value was determined by median analysis. When M equals to 0.09, the best fit was obtained for three‐components fiber blends. In that case, the maximum color difference is 1.22 CIELAB units and the average computed color difference is 0.56 CIELAB units for 36 three‐components fiber blends under D65 illuminant. When M is from 0.03 to 0.06, the best fit was obtained for four‐components fiber blends. In that case, the maximum color difference is 4.48 CIELAB units and the average computed color difference is 1.02 CIELAB units for 12 four‐components fiber blends under D65 illuminant. It is demonstrated that the algorithm can be used in color matching of fiber blends. © 2009 Wiley Periodicals, Inc. Col Res Appl, 34, 108–114, 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     

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     

The feasibility of establishing new color image scales using the magnitude estimation method

Color image is one of the most important factors in art and design. In general, artists and designers apply their own personal image meanings into their work. However, the image meaning for a specific work is frequently in conflict with those of the general observer. Thus it is necessary and important to derive one set of merit color image scales which can be utilized to predict the color image meanings of works in parallel with the average person's perception and which can also serve as a guide for artists and designers. In this study, the psychophysical method (magnitude estimation method), usually used in visual measurement of color appearance, was employed to attempt to establish new color image scales to evaluate the color image meanings of works matching those of the average person. The results show that new color image scales WIP are developed, and the relativity between the latest color image scales WIP and the color attributes (say Lightness L*, Hue h, and Chroma C*) of the CIELAB color space is also discussed. The total mean value of coefficient of variation for the results of visual assessment in the experiment of evaluating the color image meanings of the 207 color specimens used, in general, is about 36, similar to that for those experiments conducted using the psychological method. Also, a good relationship between the new color image scales and the color attributes of the CIELAB color space can be found. © 2007 Wiley Periodicals, Inc. Col Res Appl, 32, 463–468, 2007