Short presentation on the use of Complexity measures like Shannon Entropy and Kolmogorov complexity in evaluating the aesthetic value of images.

1. Evaluating Art
by Measuring
Complexity
18 November 2014
Eelco den Heijer

2. Introduction
• Autonomous Evolutionary Art
• Evolving art, images; using an aesthetic measure as the fitness function
• Complexity of the image is (only) one aspect of aesthetic appeal
• Relation between Art and Complexity is unclear

6. Aesthetic Measures
• Compute aspects of beauty
• Information Complexity, Image Complexity, Processing Complexity
• Colour Harmony
• Symmetry & Balance
• Colour gradients
• Contrast

7. Shannon Entropy
• Calculate entropy of the intensity of the pixels of an image
• Liveliness of an image
• Rigau et al, 2008 - Informational aesthetics measures. IEEE Computer Graphics
and Applications, 28(2):24–34, 2008

8. Fractal Dimension
• Approximate self-similarity
• Use box-counting method
• Very difficult to ‘satisfy’ with our representation & EC parameters

9. Machado/ Cardoso
• Calculate Image Complexity (IC) and Processing Complexity (PC)
• “Images that are visually complex, but are processed easily have the highest
aesthetic value”
• Penousal Machado and Amílcar Cardoso. Computing aesthetics. In Proceedings
of the Brazilian Symposium on Artificial Intelligence, SBIA-98, pages 219–229.
Springer- Verlag, 1998.

10. Machado/ Cardoso (2)
• Image complexity
• RMS(I) = difference in pixels between original image and compressed image
(how well can you compress an image)
• Uses JPEG compressor, 75% quality setting

11. Machado/ Cardoso (3)
• Processing Complexity
• Calculates complexity at ‘multiple time points’
• Divide image into 4 equal parts, calculate processing complexity for each
part
• Estimate the processing complexity using
• Fractal compression (Machado & Cardoso)
• JPEG 2000 compression (den Heijer & Eiben)
• Run-Length Encoding (Atkins et al)

12. Facticity
• “Entropy and Kolmogorov complexity do not necessarily measure the
interestingness of a system of a data set”
• Describes the amount of meaningful information of a dataset
• Pieter W. Adriaans. Between order and chaos: The quest for meaningful
information. Theory Comput. Syst., 45(4):650–674, 2009

18. Discussion
• The use of simple complexity estimation tools is merely the beginning in
calculating aesthetic appreciation
• How does the brain process complexity?
• And how is this linked to aesthetic value?
• Processing fluency theory (Reber, 2004)
• We probably need better models of human visual processing

19. Questions?
eelcodenheijer@gmail.com