Abstract:Color theme (palette) is a collection of color swatches for representing or describing colors in a visual design or an image. Color palettes have broad applications such as serving as means in automatic/semi-automatic design of visual media, as measures in quantifying aesthetics of visual design, and as metrics in image retrieval, image enhancement, and color semantics. In this paper, we suggest an autonomous mechanism for extracting color palettes from an image. Our method is simple and fast, and it works on … Show more
“…It rather argues achievements in identifying a novel application of color adjustment and developing a simple and concise solution that satisfies the needs of users without any user input. In terms of its methodological approach, an active engagement of human perception, particularly the perception of design‐experts, is yet been investigated fully despite recent studies have shown notable achievement in relation to color . It is expected that the full‐automation of our method largely reduces the tedious and time‐consuming tasks, which even well‐trained experts rarely evade.…”
Section: Discussionmentioning
confidence: 99%
“…In terms of its methodological approach, an active engagement of human perception, particularly the perception of design-experts, is yet been investigated fully despite recent studies have shown notable achievement in relation to color. 52,58,59 It is expected that the full-automation of our method largely reduces the tedious and time-consuming tasks, which even well-trained experts rarely evade.…”
Section: Technical Aspects To Be Improvedmentioning
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.
K E Y W O R D Scolor transfer, harmony, hue similarity, image color adjustment, visual design
| I NT ROD UCTI ONImage adjustment encompasses a wide range of techniques, such as photo quality enhancement, color adjustment, and image stitching. In particular, editing colors in an image has received extensive attention due to the compelling power of colors upon the aesthetics and impressions of an image. A number of methods have been proposed to modify the colors based on reference images, color palettes, and users' manual inputs. By transferring the colors of one image to another, these methods aim at resembling the look and/or style of given examples.In the practice of visual design, however, color adjustment is often performed with a distinct purpose in mind. For instance, designers are frequently asked to perform a series of design works related to a corporate identity or a brand. 1,2 In such tasks, the use of color is constrained by the brand identity. [3][4][5] Figure 1 shows design cases for international companies or organizations. As shown, a specific color or a color theme is dominantly used throughout the design works. In order to communicate their identity persuasively, it is important to use images that can create aesthetics and a visual harmony with the color. These examples imply a need for image adjustment in consideration of harmony with a given color. However, harmonious image adjustment has yet to be investigated, despite its practicality and usefulness in various applications.In this regard, we made a novel attempt to develop an algorithm that adjusts the colors of an image to achieve harmony with a target color. To achieve this goal, we first benchmarked the image adjustment process of designers and built a framework of our image adjustment method based on their insights. We developed its details by adopting the technical approaches of earlier color transfer studies. Finally, a user test was carried out to examine the performance of our method in the context of graphic design.Thro...
“…It rather argues achievements in identifying a novel application of color adjustment and developing a simple and concise solution that satisfies the needs of users without any user input. In terms of its methodological approach, an active engagement of human perception, particularly the perception of design‐experts, is yet been investigated fully despite recent studies have shown notable achievement in relation to color . It is expected that the full‐automation of our method largely reduces the tedious and time‐consuming tasks, which even well‐trained experts rarely evade.…”
Section: Discussionmentioning
confidence: 99%
“…In terms of its methodological approach, an active engagement of human perception, particularly the perception of design-experts, is yet been investigated fully despite recent studies have shown notable achievement in relation to color. 52,58,59 It is expected that the full-automation of our method largely reduces the tedious and time-consuming tasks, which even well-trained experts rarely evade.…”
Section: Technical Aspects To Be Improvedmentioning
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.
K E Y W O R D Scolor transfer, harmony, hue similarity, image color adjustment, visual design
| I NT ROD UCTI ONImage adjustment encompasses a wide range of techniques, such as photo quality enhancement, color adjustment, and image stitching. In particular, editing colors in an image has received extensive attention due to the compelling power of colors upon the aesthetics and impressions of an image. A number of methods have been proposed to modify the colors based on reference images, color palettes, and users' manual inputs. By transferring the colors of one image to another, these methods aim at resembling the look and/or style of given examples.In the practice of visual design, however, color adjustment is often performed with a distinct purpose in mind. For instance, designers are frequently asked to perform a series of design works related to a corporate identity or a brand. 1,2 In such tasks, the use of color is constrained by the brand identity. [3][4][5] Figure 1 shows design cases for international companies or organizations. As shown, a specific color or a color theme is dominantly used throughout the design works. In order to communicate their identity persuasively, it is important to use images that can create aesthetics and a visual harmony with the color. These examples imply a need for image adjustment in consideration of harmony with a given color. However, harmonious image adjustment has yet to be investigated, despite its practicality and usefulness in various applications.In this regard, we made a novel attempt to develop an algorithm that adjusts the colors of an image to achieve harmony with a target color. To achieve this goal, we first benchmarked the image adjustment process of designers and built a framework of our image adjustment method based on their insights. We developed its details by adopting the technical approaches of earlier color transfer studies. Finally, a user test was carried out to examine the performance of our method in the context of graphic design.Thro...
“…This method tends to select various colors to span the different conspicuous colors in the three-dimensional (3D) scatter plot of the image pixels. 20 The colors extracted by this method may not be the most salient color in one cue in the 3D scatter plot. Figure 9.Comparison with the saliency-based method proposed by Jahanian et al.…”
Section: Experiments and Evaluationmentioning
confidence: 99%
“…Figure 9.Comparison with the saliency-based method proposed by Jahanian et al. 20 The first color theme is extracted by Jahanian et al.’s method and the last is extracted by our model. (Color online only.…”
Color configuration plays an important role in art, design, and communication, which can influence the user’s experiences, feelings, and psychological well-being. It is laborious to manually select a color theme from scratch for handling large batches of images. Alternatively, it can inspire designers’ creations and save their time as well by leveraging the color themes in existing art works (e.g. fabric, paintings). However, it is challenging to automatically extract perceptually plausible color themes from fabric images. This paper presents a new automatic framework for extracting color themes from fabric images. A saliency map is built to help recognize the visual attention regions of the input image. Since the saliency map separates the image into visual attention regions (foreground) and non-visual attention regions (background), we respectively compute the dominant colors of these two regions, and merge them to form the initial target color theme based on certain rules. The dominant colors are extracted, accounting for the characteristics of the fabric and hue distributions of fabric images so as to acquire visually plausible results. Our method can be used to transfer colors between two fabric images for fabric color design. We tested our method thoroughly with various fabric images (e.g. cotton, silk, and linen) with different texture patterns (e.g. plain and twill). Experiments show that our method is more efficient and can generate more visually plausible results than state-of-the-art algorithms.
“…Often colour palettes are generated by designers for practical application based on their knowledge of aesthetics with respect to either a design brief or the designer's own colour preferences . Colour palettes may be extracted automatically from an image or a set of images or even generated from a word . There are currently no established methods for predicting the visual similarity or visual difference between two colour palettes; the automated design systems that are being developed based on data and machine learning will require the ability to be able to predict similarity between colour palettes …”
This work is concerned with the prediction of visual colour difference between pairs of palettes. In this study, the palettes contained five colours arranged in a horizontal row. A total of 95 pairs of palettes were rated for visual difference by 20 participants. The colour difference between the palettes was predicted using two algorithms, each based on one of six colour‐difference formulae. The best performance (r2 = 0.86 and STRESS = 16.9) was obtained using the minimum colour‐difference algorithm (MICDM) using the CIEDE2000 equation with a lightness weighing of 2. There was some evidence that the order (or arrangement) of the colours in the palettes was a factor affecting the visual colour differences although the MICDM algorithm does not take order into account. Application of this algorithm is intended for digital design workflows where colour palettes are generated automatically using machine learning and for comparing palettes obtained from psychophysical studies to explore, for example, the effect of culture, age, or gender on colour associations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
