Research on Visual Perception Feature Extraction of Textile Color Matching and Clothing Display Optimization Strategies

Color is the most direct visual attribute of apparel products and plays an important role in attracting consumer attention, conveying brand concepts, and stimulating purchasing interest in terminal displays. This study develops an optimal color-matching method for apparel display by combining quantitative color analysis with visual perception experiments. Common apparel display images are first collected, and the main hue, contrast, and spatial distribution characteristics of color samples are extracted in HSV color space to form a quantitative description system for color matching. Because apparel color perception depends on visible-spectrum optical interaction and image feature extraction, the method provides an engineering-oriented basis for evaluating visual display effects. A visual perception experiment is then designed in which participants judge the visual saliency, harmony, and preference of different color matching patterns. Correlation analysis is used to explore the internal relationship between quantitative color characteristics and consumer visual perception, and targeted color optimization strategies for apparel displays are proposed. The results show that hue-difference ratio and brightness-difference ratio are positively correlated with visual saliency, while color matching with similar saturation is more likely to obtain higher harmony scores. Adjacent color matching based on the main hue receives higher preference scores, whereas high-purity complementary matching attracts attention rapidly but shows lower harmony.