Attribute analysis and modeling of color harmony based on multi-color feature extraction in real-life scenes.

Color harmony is the focus of many researchers in the field of art and design, and its research results have been widely used in artistic creation and design activities. With the development of signal processing and artificial intelligence technology, new ideas and methods are provided for color harmony theory and color harmony calculation. In this article, psychological experimental methods and information technology are combined to design and quantify the 16-dimensional physical features of multiple colors, including multi-color statistical features and multi-color contrast features. Eighty-four subjects are invited to give a 5-level score on the degree of color harmony for 164 multi-color materials selected from the screenshots of film and television scenes. Based on the multi-color physical features and the subjective evaluation experiment, the correlation analysis is firstly carried out, which shows that the overall lightness, difference of the color tones, number of multiple colors, lightness contrast, color tone contrast, and cool/warm contrast are significantly correlated with color harmony. On the other hand, the regression prediction model and classification prediction model of color harmony are constructed based on machine learning algorithms. In terms of regression prediction model, the prediction accuracy of linear models is higher than that of nonlinear models, with 63.9% as the highest, indicating that the multi-color physical features can explain color harmony well. In terms of classification prediction model, the Random Forest (RF) has the best prediction performance, with an accuracy of 80.2%.

Color harmony represented by activity in the medial orbitofrontal cortex and amygdala.

Observing paired colors with a different hue (in terms of chroma and lightness) engenders pleasantness from such harmonious combinations; however, negative reactions can emerge from disharmonious combinations. Currently, neural mechanisms underlying the esthetic and emotional aspects of color perception remain unknown. The current study reports evidence regarding the neural correlates of color harmony and disharmony. Functional magnetic resonance imaging was used to assess brain regions activated by harmonious or disharmonious color combinations in comparison to other stimuli. Results showed that the left medial orbitofrontal cortex (mOFC) and left amygdala were activated when participants observed harmonious and disharmonious stimuli, respectively. Taken together, these findings suggest that color disharmony may depend on stimulus properties and more automatic neural processes mediated by the amygdala, whereas color harmony is harder to discriminate based on color characteristics and is reflected by the esthetic value represented in the mOFC. This study has a limitation that we could not exclude the effect of preference for color combination, which has a strong positive correlation with color harmony.