The Fabric Narrative of “Home”: The Local Expression of Women's Red Art in Community Public Buildings
DOI:
https://doi.org/10.70917/ijcisim-2026-0389Keywords:
female red art; K-means clustering; PCCS color system; fabric narrative; locality; community public buildingsAbstract
As an important form of traditional Chinese women's handicraft art, women's red carries rich cultural significance. In modern context, its regeneration and expression in public space, especially through the fabric narrative into the community architectural environment, has become an important medium connecting historical memory and contemporary expression, with the dual value of cultural heritage and spatial identity. This paper explores the path of local expression of women's red art in community public buildings through digital image processing and color analysis. The study firstly collects and pre-processes 152 images of women's red fabrics in different periods, extracts representative colors through K-means clustering algorithm combined with PCCS color system, and further analyzes the distribution of hue, brightness and saturation. The results show that the colors of women's red fabrics are dominated by red and blue, accounting for 50.16% and 30.82%, respectively; the brightness is concentrated in the middle and high range, accounting for 93.42%; and the strong hue is dominated, accounting for 27.41%. On this basis, the evaluation system of community public buildings' locality composed of 24 indicators was constructed, and the AHP method was used to complete the indicator assignment and validity test. 268 valid questionnaires were recovered from the empirical research of Y community, and the scoring results showed that the total evaluation score was 4.275, which verified the applicability of the system and the effectiveness of the art of women's red art to create the atmosphere of “home” in the space. The validity of the system and the effectiveness of female red art in creating the atmosphere of “home” in the space is verified.
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Copyright (c) 2026 Yi Yan, Deng Yue, Xie Shu Bin

This work is licensed under a Creative Commons Attribution 4.0 International License.