Tarozo Mateus M, Pessa Arthur A B, Zunino Luciano, Rosso Osvaldo A, Perc Matjaž, Ribeiro Haroldo V
Departamento de Física, Universidade Estadual de Maringá, Maringá, PR 87020-900, Brazil.
Centro de Investigaciones Ópticas (CONICET La Plata - CIC - UNLP), Gonnet, La Plata 1897, Argentina.
PNAS Nexus. 2025 Mar 18;4(3):pgaf092. doi: 10.1093/pnasnexus/pgaf092. eCollection 2025 Mar.
Quantitative analysis of visual arts has recently expanded to encompass a more extensive array of artworks due to the availability of large-scale digitized art collections. Consistent with formal analyses by art historians, many of these studies highlight the significance of encoding spatial structures within artworks to enhance our understanding of visual arts. However, defining universally applicable, interpretable, and sufficiently simple units that capture the essence of paintings and their artistic styles remains challenging. Here, we examine ordering patterns in pixel intensities within two-by-two partitions of images from nearly 140,000 paintings created over the past 1,000 years. These patterns, categorized into 11 types based on arguments of continuity and symmetry, are both universally applicable and detailed enough to correlate with low-level visual features of paintings. We uncover a universal distribution of these patterns, with consistent prevalence within groups, yet modulated across groups by a nontrivial interplay between pattern smoothness and the likelihood of identical pixel intensities. This finding provides a standardized metric for comparing paintings and styles, further establishing a scale to measure deviations from the average prevalence. Our research also shows that these simple patterns carry valuable information for identifying painting styles, though styles generally exhibit considerable variability in the prevalence of ordinal patterns. Moreover, shifts in the prevalence of these patterns reveal a trend in which artworks increasingly diverge from the average incidence over time; however, this evolution is neither smooth nor uniform, with substantial variability in pattern prevalence, particularly after the 1930s.
由于大规模数字化艺术藏品的可得性，视觉艺术的定量分析近来已扩展到涵盖更广泛的一系列艺术品。与艺术史学家的形式分析一致，这些研究中有许多都强调了对艺术品中的空间结构进行编码对于增进我们对视觉艺术理解的重要性。然而，定义出普遍适用、可解释且足够简单的单元来捕捉绘画及其艺术风格的本质仍然具有挑战性。在此，我们研究了过去1000年创作的近140,000幅绘画图像的二乘二分区内像素强度的排序模式。这些模式根据连续性和对称性的论点被分为11种类型，它们既普遍适用又足够详细，能够与绘画的低层次视觉特征相关联。我们发现了这些模式的一种普遍分布，在各群体内部具有一致的流行程度，但在不同群体之间，由于模式平滑度与相同像素强度可能性之间的复杂相互作用而受到调节。这一发现为比较绘画和风格提供了一种标准化指标，进一步建立了一个衡量与平均流行程度偏差的尺度。我们的研究还表明，这些简单模式携带了用于识别绘画风格的有价值信息，尽管不同风格在有序模式的流行程度上通常表现出相当大的变异性。此外，这些模式流行程度的变化揭示了一种趋势，即随着时间推移，艺术品与平均发生率的差异越来越大；然而，这种演变既不平稳也不均匀，模式流行程度存在很大变异性，特别是在20世纪30年代之后。
