Color Research and Application最新文献

Color matching is a key element in product design that forms visual harmony, emotional connection, and spatial perception. As perfect balance between aesthetic value and perceptual continuity is still difficult to attain in view of differences in individual perception of color, this research seeks to provide a systematic and quantifiable approach to understanding how combinations of colors affect emotional expression and visual beauty in mechanical product design. The research uses the Aesthetic Measurement Model (AMM) with Markov decision-making theory to analyze 125 color palettes that fully cover the applied color coordinate system. The aesthetic measure theory is used to identify the unity and coherence of color aesthetics, and Markov decision theory is used to identify the connection among mechanical product images and color combinations, which results in five symbolic color variations from two representative samples. Statistical verification enhances the reliability and stability of results, validating the method connecting quantitative and qualitative color ratings. The AMM-Markov decision-making theory achieved a predictive accuracy of 96.5%, surpassing existing analyses and demonstrating improved capability in assessing product aesthetic quality. The research advances color-based design methods by integrating aesthetic measurement with decision-theoretic modeling, enhancing emotional appeal, visual beauty, and overall design quality of mechanical products.

Modeling the quantitative relationship between physical measurements and human perception offers a research-driven guide for mass customization and personalization of products. In China, individuals often select liquid foundation to improve skin whiteness when applying makeup, but there is currently no quantitative research on this preference for whiteness. The aim of this study is to investigate the quantitative impact of the whiteness index on the color preference of liquid foundation and to examine the relationship between individual skin tone and color preference evaluation. A total of 495 women, aged 18–40, from Shanghai, were included in this study. Ten popular liquid foundation colors were formulated by professional colorists from cosmetics companies. Facial skin color was measured using VISIA 7, and the results of subjective color evaluations across different skin tone groups were statistically analyzed to explore the influence of individual skin tone on color preference. The findings revealed that the whiteness scale of liquid foundation and subjective preference evaluation achieved the highest fitting result (R² = 0.97 for nonlinear fitting), suggesting that the whiteness index is the optimal metric for evaluating the color preference of foundation. Meanwhile, variations in color preference evaluation results for liquid foundation were observed across different skin tone groups. Finally, a color preference evaluation model based on individual skin tone grouping was established, with an R² value of 0.93.

Harmonious color combinations define the quality and atmosphere of interior spaces. Designers refine schemes through iteration to meet client requirements, often relying on existing color design tools. However, these tools have two key limitations: they do not account for colors applied to specific objects, nor do they reflect aesthetic preferences. To address this, we developed a vision-language augmented Image Color Aesthetic Assessment model that predicts color compatibility for objects in interior design images. Moreover, this model powers the crowd-based Image Color Combination Evaluation system, enabling designers to prototype, evaluate, and generate new color combinations in real time. A user study with 16 designers revealed that 81% found the predicted color compatibility scores aligned with aesthetic principles with which they were familiar, aiding them in integrating these scores into their designs. The proposed system helps designers explore harmonious color combinations, avoid personal bias, and foster trust by leveraging predicted crowd-based color compatibility.

Fairchild has argued that color spaces are of questionable utility for understanding perception. Here, we go through various concepts of mathematical spaces, ranging from abstract topological spaces to Euclidean ones, and discuss how color stimuli, color matches, and color perceptions can be adequately represented by means of some of these spaces. In particular, we argue that the set of color perceptions can be represented as a metric space that is homeomorphic to a neither open nor closed convex cone in an n-dimensional Banach space of equivalence classes of “generalized metamers.” Finally, for higher color metrics, we sketch how Riemannian geometry can be used to create a unified representation of color stimuli and color perceptions.

Color systems and atlases are critical tools for defining, organizing, and communicating colors across industrial, scientific, and artistic domains. While widely adopted systems—including Munsell, Natural Color System (NCS), DIN, Coloro, Pantone Fashion, Home + Interiors numbering system (Pantone FHI), and Sino Color Book (SCB)—leverage distinct organizational principles and application-specific advantages, their step sizes (spacing between adjacent chips) and uniformity (consistency of spacing) have not been compared. This study evaluates these metrics using four color difference formulas (CIELAB, CMC, CIEDE2000, and CAM16-UCS) to quantify step sizes and the coefficient of variation (CV) to assess uniformity. In terms of step size, key findings reveal that Coloro achieves the smallest median step size (with CIELAB values of 2.2, 1.6, and 1.8 in the Hue, Lightness, and Chroma attributes, respectively), but contains only a limited number of adjacent pairs. SCB ranks second (with CIELAB values of 2.0, 3.0, and 2.2 in the Hue, Depth, and Chroma attributes, respectively), yet it comprises a substantially larger number of pairs. In terms of uniformity, SCB exhibits superior uniformity in the Hue attribute. Both Munsell and DIN excel in uniformity in the Value/Darkness attribute. NCS leads in uniformity for the Chroma attribute. Crucially, no single system and atlas optimize across all attributes. These findings clarify system-specific strengths and highlight the challenge of integrating these strengths into a unified color system, while providing a foundation for future research in color order systems.

Much of the current research on display chromatic adaptation has predominantly used neutral colors as stimuli, while memory colors—critical for natural scene perception but under-researched—have been largely overlooked. Memory colors refer to the typical colors that are consistently associated with familiar objects in long-term memory (e.g., sky blue, skin tones). Given that users primarily interact with chromatic images rather than uniform neutral fields, distinct adaptation mechanisms may exist for these two stimulus categories. This study systematically investigates human chromatic adaptation to computer displays under 20 controlled adaptation conditions (correlated color temperature, CCT, from 2890 to 9000 K in five steps; deviation from the Planckian locus, Duv, from −0.02 to +0.02 in four steps) using both neutral and memory color stimuli. The results revealed that the degree of chromatic adaptation for both neutral and memory colors increased with higher CCT and that the relative magnitude of the D values for both types of stimuli was modulated by stimulus luminance. For the conditions with a same CCT, a Duv of +0.02 was found to provide a higher degree of chromatic adaptation, which differs from the findings in studies with neutral colors. The results were also used as corresponding colors to derive models of the degree of chromatic adaptation.