Color Research and Application最新文献

As the optical fingerprint that reflects the physiological states of skin, the accurate acquisition of skin spectral reflectance is crucial for pathological diagnosis, ensuring digital imaging fidelity, and enabling the quantitative evaluation of cosmetic efficacy. This paper surveys the advancements in skin spectral reflectance measurement techniques and their applications. Regarding measurement methods, spectrophotometry (250–2500 nm) delivers high-precision single-point data, while hyperspectral imaging (400–1000 nm) enables spatially resolved spectral analysis for applications like skin cancer detection, albeit with higher costs and lower imaging efficiency. Meanwhile, computational spectral imaging leverages RGB reconstruction to achieve high spatial resolution, though metamerism and generalizability limitations remain unresolved. In the field of skin reflectance applications, current efforts focus on three domains of medical diagnostics (e.g., dermatitis grading and blood oxygen monitoring), digital imaging (e.g., skin tone correction), and cosmetic technology (e.g., dark circle assessment, efficacy testing of cosmetics, and beauty device development). Despite these innovations, limitations such as measurement errors on uneven skin, high equipment costs, hardware constraints, and operational inconsistencies in skin tone calibration continue to pose significant barriers. To overcome these limitations, we proposed leveraging compressed sensing for efficient hardware-level data acquisition and physics-constrained meta-learning algorithms to enhance generalizability. This survey offers insights for advancing skin spectral measurement technologies and their analytical applications.

The display of traditional Chinese paintings in museums requires lighting that maximizes the true color rendering of the artwork. This necessitates high requirements for the lighting source, including the fidelity index (R_f) and the gamut index (R_g) to ensure natural color rendering. However, due to the unique colors of traditional Chinese paintings and the specific lighting conditions of exhibition halls (low illumination and high brightness contrast), the optimal lighting index thresholds for these paintings are not yet clear. In this study, a 1:1 simulated museum environment for exhibiting traditional Chinese paintings was constructed. Four CCT conditions were established, each incorporating 12 combinations of R_f and R_g, resulting in 48 experimental lighting conditions. Four representative traditional Chinese paintings with distinct color characteristics were selected as evaluation objects. A psychophysical subjective evaluation experiment on the perceived color naturalness of these paintings was conducted with 34 participants. Data analysis revealed the respective effects of R_f and R_g on color naturalness under each CCT condition, as well as recommended R_f and R_g ranges to ensure optimal color rendering. Specifically, light sources with R_f ≥ 95 are preferred. When R_f < 95, light sources with R_g ≥ 100 are most likely to preserve high perceived color naturalness. This study provides a basis for selecting appropriate light sources and establishing relevant standards for lighting traditional Chinese paintings in museums.

Color expression in children's illustrations plays a vital role in the display. Children can enjoy the colors and experience the emotion conveyed by the illustration theme through their perception of color. Based on the K-means clustering algorithm and color network, this paper analyzed color clustering of children's illustration samples with the theme of “Spring” and constructed a color network model for these samples. Using the semantic difference method and Likert scale, a semantic division questionnaire was developed to derive representative vocabulary for the illustration samples. The color systems obtained from clustering were then matched with the representative vocabulary to form a color perceptual analysis questionnaire. Through factor analysis, typical vocabularies were identified, and corresponding color systems were created as experimental illustration samples. This paper explores the expressive forms of color systems under different vocabularies and verifies the feasibility and reliability of the experimental illustration samples within the target group, thereby providing new directions and references for color design and color education in children's illustrations.

Museum lighting for paintings collected in Chinese museums, which represent traditional color aesthetics, must balance both the protection of the collection and the enhancement of visual quality to convey the paintings' value, particularly the perception of color naturalness under varying lighting conditions. This study simulated museum lighting environments in a variable space experimental chamber, using representative cold and warm tone Chinese freehand paintings as experimental subjects. Lighting conditions were varied according to three parameters: ambient illuminance (E), the fidelity of the light source (R_f), and the saturation of the light source (R_g). Color naturalness scores for the paintings were obtained through a subjective evaluation by 30 participants. The results show that increasing the ambient illumination, that is, reducing the contrast in illumination between inside and outside the display case, helps improve observers' ratings of the naturalness of the painting colors and reduces the impact of R_f and R_g on these ratings, thereby expanding the range of selectable light source parameters. When ambient illuminance was low, increasing R_f improved color naturalness, and a moderate R_g value more effectively restored the colors of the paintings. Through multiple linear regression analysis, the model for evaluating the color naturalness of cold and warm tone paintings was established, that is, the color naturalness scores of the paintings could be predicted based on the three lighting parameters. This model provides a scientific framework for optimizing the lighting design of paintings collected in museums, benefiting both the preservation and promotion of Chinese traditional culture.

This study examines the impact of low-saturation background colors on working memory through a detailed multimodal analysis involving functional near-infrared spectroscopy (fNIRS), eye tracking, and subjective assessments. The aim is to identify colors that enhance or impede cognitive performance and uncover the physiological mechanisms involved. Thirty-eight participants completed a 2-back working memory task under nine different background color conditions, during which cognitive performance, brain activation patterns, and eye movement data were systematically recorded. The findings indicate that low-saturation cyan backgrounds significantly enhance cognitive performance by facilitating faster response times and higher accuracy, suggesting these colors help reduce cognitive strain. Conversely, red and purple backgrounds appear to increase cognitive load, slowing response times, and reducing accuracy. Increased activation in the dorsolateral prefrontal cortex was observed under cyan and blue backgrounds, correlating with improved cognitive metrics. While statistical analyses confirmed the impact of low-saturation background color on cognitive and physiological responses, the correlation analyses suggested a more nuanced relationship. Longer response times were associated with higher accuracy, especially in less optimal color conditions, indicating a possible compensatory mechanism to maintain performance. These findings highlight the potential of strategic color use to enhance cognitive function, with important implications for optimizing work and learning environments to more effectively support cognitive task performance. Further investigations should widen the scope of colors studied and consider different cognitive tasks to deepen the understanding of the role of color in cognitive environments, aiming to refine design strategies for optimal cognitive support.

Semantic color association is a nuanced process shaped by factors such as context, culture, and individual demographics. Designers invest significant effort in selecting color palettes that evoke intended emotional responses and resonate with their target audience. One widely used framework in design education and industry is the Color Image Scale (CIS), developed by Shigenobu Kobayashi in 1989. Grounded in a Japanese cultural context, CIS organizes color palettes along three perceptual axes—warm–cool (hue), soft–hard (tone), and clear–grayish (chroma)—and associates these with emotional adjectives. While influential, the CIS was based initially on a constrained sampling of Japanese participants, raising questions about its applicability to other cultural settings. This study aims to test and adapt Kobayashi's CIS framework within a North American cultural context situated within the United States through a multiphase research approach. Specifically, we examine how contemporary United States designers and non-designers interpret color-semantic associations compared to the original Japanese dataset. To this end, the researchers developed an online survey to gather insights on word associations by collecting responses to single-hue and three-hue color palette samples. The findings provide insight into culturally situated semantic color associations and demonstrate meaningful differences between the original CIS model in semantic alignment across demographics and professional backgrounds. This research contributes to the cross-cultural validation of the CIS and lays the groundwork for developing updated tools that reflect the semantic and aesthetic preferences of American audiences situated in the United States.