Topological invariants can be used to quantify complexity in abstract paintings

A method is proposed to quantify complexity in abstract art.Topological invariants, the Betti numbers, are used.The method is tested with the paintings of Jackson Pollock.Comparisons with other art pieces show the uniqueness of Pollocks paintings. Abstract art screams of complexity: its visual language purposely creates complex images that are a distorted artist-driven vision of the real world. Complexity can be recognized from either the composition, form, color, brightness, among other aspects. In this paper we show that it is possible to objectively assess the complexity of abstract paintings by determining the values of the Betti numbers associated with the image. These quantities, which are topological invariants, capture the amount of connectivity and spatial distribution of the paint traces. We apply this analysis to a series of abstract paintings, demonstrating that the complexity of Jackson Pollock paintings produced by his famous dripping technique, is superior compared with many other abstract paintings by different authors. Opposed to what was previously discussed considering only fractal properties, the complexity does not simply increase with time; instead, it displays a local maximum at a certain year which coincides with the time when Pollock perfected his technique. This tool has been used before to measure complexity in other scientific areas, but not for art assessment.

[1]  E. M. De la Calleja,et al.  Order-fractal transitions in abstract paintings , 2016 .

[2]  David J Field,et al.  Statistical regularities of art images and natural scenes: spectra, sparseness and nonlinearities. , 2007, Spatial vision.

[3]  Philip K. Maini,et al.  Turbulent Luminance in Impassioned van Gogh Paintings , 2007, Journal of Mathematical Imaging and Vision.

[4]  C. Redies,et al.  Beauty in abstract paintings: perceptual contrast and statistical properties , 2014, Front. Hum. Neurosci..

[5]  Kelin Xia,et al.  Persistent homology analysis of protein structure, flexibility, and folding , 2014, International journal for numerical methods in biomedical engineering.

[6]  D. Thouless,et al.  Ordering, metastability and phase transitions in two-dimensional systems , 1973 .

[7]  Alison Abbott Fractals and art: In the hands of a master , 2006, Nature.

[8]  L. Göttsche The Betti numbers of the Hilbert scheme of points on a smooth projective surface , 1990 .

[9]  Richard Taylor,et al.  Authenticating Pollock paintings using fractal geometry , 2007, Pattern Recognit. Lett..

[10]  G. J. Burton,et al.  Color and spatial structure in natural scenes. , 1987, Applied optics.

[11]  Joachim Denzler,et al.  Fractal-like image statistics in visual art: similarity to natural scenes. , 2007, Spatial vision.

[12]  Harsh Mathur,et al.  Drip paintings and fractal analysis. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[13]  Vladimir A. Kovalevsky,et al.  Finite topology as applied to image analysis , 1989, Comput. Vis. Graph. Image Process..

[14]  Richard Taylor,et al.  The Abstract Expressionists and Les Automatistes: A shared multi-fractal depth? , 2013, Signal Process..

[15]  J. C. Budich,et al.  Topological aspects of π phase winding junctions in superconducting wires , 2015, Journal of physics. Condensed matter : an Institute of Physics journal.

[16]  J R Mureika,et al.  Multifractal structure in nonrepresentational art. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[17]  Yang Wang,et al.  Multifractal analysis and authentication of Jackson Pollock paintings , 2008, Electronic Imaging.

[18]  James R. Munkres,et al.  Elements of algebraic topology , 1984 .

[19]  Richard P. Taylor,et al.  Fractal analysis of Pollock's drip paintings , 1999, Nature.

[20]  Richard P Taylor Order in Pollock's chaos. , 2002, Scientific American.

[21]  Kevin W Eliceiri,et al.  NIH Image to ImageJ: 25 years of image analysis , 2012, Nature Methods.

[22]  S F Chipman,et al.  Influence of six types of visual structure on complexity judgments in children and adults. , 1979, Journal of experimental psychology. Human perception and performance.

[23]  H J Eysenck,et al.  An experimental study of aesthetic preference for polygonal figures. , 1968, The Journal of general psychology.

[24]  Konstantin Mischaikow,et al.  Topology of force networks in compressed granular media , 2012 .

[25]  Harsh Mathur,et al.  Fractal Analysis: Revisiting Pollock's drip paintings , 2006, Nature.

[26]  C. Cela-Conde,et al.  Predicting beauty: fractal dimension and visual complexity in art. , 2011, British journal of psychology.

[27]  Richard M. Nicki,et al.  Preference for non-representational art as a function of various measures of complexity. , 1975 .

[28]  J R Mureika,et al.  Fractal dimensions in perceptual color space: a comparison study using Jackson Pollock's art. , 2005, Chaos.