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<p>This study quantifies chromatic evolution in flower-and-bird painting across traditional, modern, and contemporary periods by integrating computational color analysis with art-historical interpretation. A curated image dataset is analyzed using perceptual color difference (ΔE2000), Sinkhorn Optimal Transport, bootstrap resampling, and community detection. Motif-aware palette separation enables comparison between floral and avian color distributions within and across eras. Results show that traditional works exhibit lower transport costs and smaller ΔE2000 distances, indicating higher chromatic harmony and symbolic consistency, whereas modern and contemporary works display increased palette dispersion and variability. Bootstrap inference confirms the robustness of these differences under severe class imbalance. Community detection reveals distinct chromatic groups corresponding to historical styles and transitional practices, quantitatively supporting theories of symbolic color coding for motifs such as peony and orchid. Overall, the study demonstrates that tailored computational metrics reproducibly capture stylistic divergence and cultural continuity, bridging color science and art-historical analysis.</p>

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Comparative study of color in traditional and contemporary flower and bird paintings

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月26日

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  • Cheng Zhang

摘要

This study quantifies chromatic evolution in flower-and-bird painting across traditional, modern, and contemporary periods by integrating computational color analysis with art-historical interpretation. A curated image dataset is analyzed using perceptual color difference (ΔE2000), Sinkhorn Optimal Transport, bootstrap resampling, and community detection. Motif-aware palette separation enables comparison between floral and avian color distributions within and across eras. Results show that traditional works exhibit lower transport costs and smaller ΔE2000 distances, indicating higher chromatic harmony and symbolic consistency, whereas modern and contemporary works display increased palette dispersion and variability. Bootstrap inference confirms the robustness of these differences under severe class imbalance. Community detection reveals distinct chromatic groups corresponding to historical styles and transitional practices, quantitatively supporting theories of symbolic color coding for motifs such as peony and orchid. Overall, the study demonstrates that tailored computational metrics reproducibly capture stylistic divergence and cultural continuity, bridging color science and art-historical analysis.