Dark mode has become a standard feature across digital interfaces due to its visual comfort and aesthetic appeal. However, most brand logos are originally designed for light backgrounds, and when directly applied to dark backgrounds, they often suffer from color distortion, reduced visibility, and visual discomfort. These issues can negatively impact both brand identity and user experience. This study aims to propose a systematic adjustment model to optimize brand logo colors in dark mode environments. The research consisted of two experiments. In the first experiment, 31 design-major students manually adjusted 18 fictitious logos with diverse colors on a black background. The analysis revealed systematic trends in color modification, with bright colors shifting toward darker values, dark colors becoming lighter, and chroma showing an overall reduction. Additionally, red and blue hues required hue-angle corrections. Based on these findings, a convergence surface for color adjustment was constructed using Kriging interpolation, leading to the development of a predictive model applicable to new logo colors. The second experiment evaluated the model through a preference survey with 89 participants, using a set of 36 logos, including 18 fictitious logos and 18 commercial logos. Participants compared original logos with those adjusted by the proposed model. The adjusted versions were generally preferred, with the effect being particularly pronounced for logos originally featuring dark colors. The proposed model offers design principles that ensure both brand consistency and visual comfort. By integrating perceptual evidence with empirical validation, this approach provides a stable method for maintaining brand color representation in digital environments and demonstrates applicability to a wider range of graphic elements in dark mode.
Kim et al. (Thu,) studied this question.