Large-Scale Quantitative Analysis of Painting Arts

Daniel Kim, Seung‐Woo Son, Hawoong Jeong

Scientific Reports · 2014 · 77 citations · 18 references

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Abstract

Scientists have made efforts to understand the beauty of painting art in their own languages. As digital image acquisition of painting arts has made rapid progress, researchers have come to a point where it is possible to perform statistical analysis of a large-scale database of artistic paints to make a bridge between art and science. Using digital image processing techniques, we investigate three quantitative measures of images – the usage of individual colors, the variety of colors and the roughness of the brightness. We found a difference in color usage between classical paintings and photographs and a significantly low color variety of the medieval period. Interestingly, moreover, the increment of roughness exponent as painting techniques such as chiaroscuro and sfumato have advanced is consistent with historical circumstances.

References

18