Literature DB >> 28279713

High entropy of edge orientations characterizes visual artworks from diverse cultural backgrounds.

Christoph Redies1, Anselm Brachmann2, Johan Wagemans3.   

Abstract

We asked whether "good composition" or "visual rightness" of artworks manifest themselves in a particular arrangement of basic image features, such as oriented luminance edges. Specifically, we analysed the layout of edge orientations in images from a collection of >1600 paintings of Western provenance by comparing pairwise the orientation of each edge in an image with the orientations of all other edges in the same image. From the resulting orientation histograms, we calculated Shannon entropy and parallelism (i.e., the degree to which lines are parallel in the image). For comparison, we analysed the same second-order image properties in photographs of diverse natural patterns and man-made objects and scenes. Results showed that Shannon entropy of relative orientations of edge pairs was high and parallelism was low for the paintings and some of the natural patterns, but differed from other sets of photographs, including other man-made stimuli. The differences were also observed when images were matched for image content. Moreover, high entropy of edge orientations was found in traditional artworks produced by different techniques, in artworks that represented different content matter and art genres, as well as in artworks from other cultural backgrounds (East Asian and Islamic). In conclusion, we found that high entropy of edge orientations characterizes diverse sets of traditional artworks from various cultural backgrounds.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Edge density; Experimental aesthetics; Image analysis; Pair-wise image statistics

Mesh:

Year:  2017        PMID: 28279713     DOI: 10.1016/j.visres.2017.02.004

Source DB:  PubMed          Journal:  Vision Res        ISSN: 0042-6989            Impact factor:   1.886


  13 in total

1.  Image statistics of the environment surrounding freely behaving hoverflies.

Authors:  Olga Dyakova; Martin M Müller; Martin Egelhaaf; Karin Nordström
Journal:  J Comp Physiol A Neuroethol Sens Neural Behav Physiol       Date:  2019-04-01       Impact factor: 1.836

2.  The Order & Complexity Toolbox for Aesthetics (OCTA): A systematic approach to study the relations between order, complexity, and aesthetic appreciation.

Authors:  Eline Van Geert; Christophe Bossens; Johan Wagemans
Journal:  Behav Res Methods       Date:  2022-09-28

3.  Statistical Image Properties in Works from the Prinzhorn Collection of Artists with Schizophrenia.

Authors:  Gudrun Maria Henemann; Anselm Brachmann; Christoph Redies
Journal:  Front Psychiatry       Date:  2017-12-11       Impact factor: 4.157

Review 4.  Computational and Experimental Approaches to Visual Aesthetics.

Authors:  Anselm Brachmann; Christoph Redies
Journal:  Front Comput Neurosci       Date:  2017-11-14       Impact factor: 2.380

5.  Using CNN Features to Better Understand What Makes Visual Artworks Special.

Authors:  Anselm Brachmann; Erhardt Barth; Christoph Redies
Journal:  Front Psychol       Date:  2017-05-23

6.  Edge-Orientation Entropy Predicts Preference for Diverse Types of Man-Made Images.

Authors:  Maria Grebenkina; Anselm Brachmann; Marco Bertamini; Ali Kaduhm; Christoph Redies
Journal:  Front Neurosci       Date:  2018-09-28       Impact factor: 4.677

7.  Gist Perception of Image Composition in Abstract Artworks.

Authors:  Kana Schwabe; Claudia Menzel; Caitlin Mullin; Johan Wagemans; Christoph Redies
Journal:  Iperception       Date:  2018-06-13

8.  Global Image Properties Predict Ratings of Affective Pictures.

Authors:  Christoph Redies; Maria Grebenkina; Mahdi Mohseni; Ali Kaduhm; Christian Dobel
Journal:  Front Psychol       Date:  2020-05-12

9.  Acute sleep loss induces signs of visual discomfort in young men.

Authors:  Olga Dyakova; Frida H Rångtell; Xiao Tan; Karin Nordström; Christian Benedict
Journal:  J Sleep Res       Date:  2019-02-27       Impact factor: 3.981

10.  Statistical Image Properties in Large Subsets of Traditional Art, Bad Art, and Abstract Art.

Authors:  Christoph Redies; Anselm Brachmann
Journal:  Front Neurosci       Date:  2017-10-25       Impact factor: 4.677

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