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Art is the ultimate expression of human creativity that is deeply influencedby the philosophy and culture of the corresponding historical epoch. Thequantitative analysis of art is therefore essential for better understandinghuman cultural evolution. Here we present a large-scale quantitative analysisof almost 140 thousand paintings, spanning nearly a millennium of art history.Based on the local spatial patterns in the images of these paintings, weestimate the permutation entropy and the statistical complexity of eachpainting. These measures map the degree of visual order of artworks into ascale of order-disorder and simplicity-complexity that locally reflectsqualitative categories proposed by art historians. The dynamical behavior ofthese measures reveals a clear temporal evolution of art, marked by transitionsthat agree with the main historical periods of art. Our research shows thatdifferent artistic styles have a distinct average degree of entropy andcomplexity, thus allowing a hierarchical organization and clustering of stylesaccording to these metrics. We have further verified that the identified groupscorrespond well with the textual content used to qualitatively describe thestyles, and that the employed complexity-entropy measures can be used for aneffective classification of artworks.

History of art paintings through the lens of entropy and complexity