Application of Partial Differential Equation Image Classification Methods to the Aesthetic Evaluation of Images

The average accuracy of the fusion of color harmony and composition features is 75.17%, which is higher than that of a single feature. The classification accuracy of NP-DP-DCNN structure is about 1% higher than that of other methods and 1.77% higher than that of NP-DCNN. Traditional image aesthetic evaluation methods are only effective for specific image sets or specific style images and are not suitable for all types of images. Based on the introduction of the partial differential equation image filtering method, through the parallel supervised learning of aesthetic attribute labels, this paper extracts the global aesthetic depth features, adopts the partial differential equation to evolve the contour C constant, and constructs a convolution neural network. The structure of a convolution kernel learned by using parallel network structure achieves better classification performance. Through the aesthetic evaluation experiment, the overall test accuracy is improved by 0.58% and the average accuracy of the integration of color harmony and composition features is 75.17%, which is higher than that of a single feature. The classification accuracy of NP-DP-DCNN structure is about 1% higher than that of other methods and 1.83% higher than that of NP-DCNN. It has achieved better test accuracy than before in the seven subcategories with discrimination between high aesthetic and low aesthetic images. It has achieved better classification performance than the traditional feature extraction methods in the public dataset CUHK database, and it has excellent aesthetic reference value.

Affective Responses to Image Color Combinations

Responses to colored patterns were collected for a group of 60 naive participants. We explicitly aimed at affective responses, rather than aesthetic judgments, so this is not ‘color harmony’ proper. Patterns were mainly spatially highly structured compositions, the color palettes reminiscent of what is found in generic ‘colorist’ art. Color combinations systematically cover mono-, di-, and trichromatic chromatic chords, whereas there was always an additional achromatic component. This sets the research apart from the bulk of the mainstream literature on ‘color harmony.’ Various ways of analysis are compared. Clustering methods reveal that the responses are highly structured through the teal–orange (cool–warm) dimension. Clustering reveals a large group of mutually concordant participants and various small, idiosyncratic groups. When the data is coarse-grained, retaining only a limited red–blue–yellow palette, the group as a whole appears quite concordant. It is evident that responses are systematic, thus the notion of a universal affective response to color combinations gains some credibility. The precise affective responses are specific because constrained by the seven categories used in the experiment. Thus, the systematic structure is perhaps to be understood as the generic result. We discuss tangencies with various traits found with ‘colorist’ art styles.

Exploration on the Application of Color Contrast and Harmony in Advertising Design

This paper briefly summarizes the principle of color contrast and color harmony, which mainly explains their applications in advertising design. From the exploration, it is found that the moderate contrast, sharp contrast and progressive contrast of color are often employed in advertising design, furthermore, the identity harmony, approximate harmony and order harmony is also widely used in advertising design. Therefore, in order to better carry out the application of color contrast and harmony, the advertising design department should actively train professionals in color, strengthen advertising design review and conduct the all-around market research.

Perception, Preference, and Prices in Josef Albers’ Square Series

Josef Albers’ Homage to the Square series comprises a vast ensemble of compositions based on similar arrays of nested squares. The main difference among these paintings is the colors employed. Therefore, they constitute an almost natural experiment to explore color preferences. We focus on the relationship between the prices paid in public auctions for these paintings and their color attributes over a fourteen-year period. We describe the attributes of the color palette using several color-related metrics aimed at capturing dominant colors, color diversity and contrast, color harmony, and color emotions. We find that color-related metrics explain a great deal of the price variation in Albers’ Squares series. Intriguingly, dominant colors and emotions are the key variables, while color harmony, contrast and diversity play no role at all. We also find that the market favors lighter tones and bluer hues. Additionally, the analyses reveal that Albers, judged by the prices commanded by his paintings, was a quintessential experimentalist ‒ as opposed to a conceptual artist. That is, an artist who kept improving as he gained more experience playing with the same concept over and over. It is worth noting that using market prices to study color preferences or judge aesthetic merits can provide different insights regarding color preferences and color perception, given the fact that most color preference studies are carried out in experimental or artificial settings, where the subjects do not have any direct interests at stake.

ColorEmo: Color Hunt with Affective Words

Color is a main channel to express emotions of an image. Selecting a good color scheme with color harmony and proper emotional expression is very important in many fields, such as design. There are many color palette tools to help users search, create, edit, save, and share color themes, but few tools are from the perspective of emotional expression and explicitly address the emotional effects of colors. In this paper, a color hunt system with affective words called ColorEmo is developed. Multiple types of input, including affective words, affective categories in image-scale space, and main colors, are allowed for users with accurate emotional description. Based on the dataset with 428,924 color themes, the system provides rich candidates. The system is designed for user research experiments. The user-friendly interactions are offered for easy color modifications. The affective matching and color harmony are evaluated in real time while changing colors. This system can be used in many scenarios of designs and applications.

The Paramaters of Visual Art Assessment as a Measurement Instrument for Learning Products of Art Painting, Sculpture, Ceramic and Batik

Assessing learning products of visual art was unlike evaluating other learning products. Due to its relation to visual outcomes, the first assessment required proper sensitiveness and measurable references. The research was intended to be the effort to acquire parameters of visual art assessment, especially of art painting, sculpture, ceramic, and batik assessments. The findings could be used as instruments in various visual art learning activities. Data were collected by distributing a list, interviewing the informants, and having Focus Group Discussion. The respondents were visual art lectures in the Faculty of Arts and Literature in one of the state universities in norther island of Sumatera, Indonesia. They were excellent at visual art and equipped with required sensitiveness. Besides, they also had relevant education with art painting, sculpture, ceramic, and batik. The findings, in the form of assessment parameters, were first, parameters of visual art assessment were form similarity, proportion, spatial depth, technique, composition, content, ambiance, brightness, color harmony, and texture. Secondly, parameters of non-figurative sculpture assessment were technique mastery, proportion, smoothness, expression, volume, space, and idea authenticity. Thirdly, parameters of figurative sculpture assessment were visual anatomy, proportion, motion effect, and drapery. Fourthly, parameters of ceramic assessment were technique mastery/finishing, innovation creativity, novelty, smoothness, expression, harmony, and need (market need). Last, parameters of batik assessment were technique, authenticity, modernity, color harmony, innovativeness, need finishing, and affordability.