Two-by-two ordinal patterns in art paintings

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.

Authors

Institutions

Publication Details

Journal
PNAS Nexus
Published
2025-02-27
DOI
https://doi.org/10.1093/pnasnexus/pgaf092
Citations
2
Primary Topic
Aesthetic Perception and Analysis
Type
article
Field-Weighted Citation Impact
2.86
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Two-by-two ordinal patterns in art paintings

Luciano Zunino, Haroldo V. Ribeiro, Matjaž Perc, Arthur A. B. Pessa et al.
2 citations
PNAS Nexus
Aesthetic Perception and Analysis
2.86
article

Two-by-two ordinal patterns in art paintings

Luciano Zunino, Haroldo V. Ribeiro, Matjaž Perc, Arthur A. B. Pessa, Osvaldo A. Rosso, Mateus M Tarozo
article en
2 citations

Abstract

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.

PNAS NexusVol. 4(3)
Universidade Estadual de Maringá (BR), Consejo Nacional de Investigaciones Científicas y Técnicas (AR), Korea University (KR), Kyung Hee University (KR), University of Maribor (SI), Zdravstveni dom dr. Adolfa Drolca Maribor (SI), Complexity Science Hub (AT), University Clinical Centre Maribor (SI), Centro de Investigaciones Cardiovasculares (AR), Universidade Federal de Alagoas (BR), Universidad Nacional de La Plata (AR)
Sustainable cities and communities
Openalex Percentile: Top 11%
Aesthetic Perception and Analysis
2.86
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.