Kolmogorov compression complexity may differentiate different schools of Orthodox iconography
Creators
- 1. Research Center for Integrated Analysis and Territorial Management, Faculty of Geography, University of Bucharest, 4-12 Regina Elisabeta Boulevard, 030018, Bucharest, Romania.
- 2. Research Center for Integrated Analysis and Territorial Management, Faculty of Geography, University of Bucharest, 4-12 Regina Elisabeta Boulevard, 030018, Bucharest, Romania. ion.andronache@geo.unibuc.ro.
- 3. GSRC, Division of Biophysics, Medical University of Graz, 8010, Graz, Austria.
- 4. Physics Department, University of Oregon, Eugene, OR, 97403, USA.
- 5. Key Research Institute of Yellow River Civilization and Sustainable Development and Collaborative Center On Yellow River Civilization, Laboratory of Yellow River Cultural Heritage, Henan University, Minglun Road 85, 475001, Kaifeng, Henan, China
- 6. Department of Experimental Oncology, Institute of Oncology and Radiology of Serbia, Pasterova 14, 11000, Belgrade, Serbia.
- 7. Mural Art Department, Faculty of Decorative Arts and Design, Bucharest National University of Arts, General Constantin Budisteanu 19, 010773, Bucharest, Romania.
- 8. Faculty of Administration and Business, University of Bucharest, 4-12 Regina Elisabeta Boulevard, 030018, Bucharest, Romania.
- 9. Faculty of Natural Sciences and Mathematics, University of Maribor, Koroška cesta 160, 2000, Maribor, Slovenia.; Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, 404332, Taiwan. ; Alma Mater Europaea, Slovenska ulica 17, 2000, Maribor, Slovenia. Complexity Science Hub Vienna, Josefstädterstraße 39, 1080, Vienna, Austria.
- 10. Center for Artificial Intelligence, Prince Mohammad Bin Fahd University, Khobar, 31952, Saudi Arabia.
- 11. Institute for Multidisciplinary Research, University of Belgrade, 1 Kneza Višeslava st., 11030, Belgrade, Serbia.
- 12. "Dumitru Stăniloae" Doctoral School, Faculty of Orthodox Theology, University of Bucharest, Sf. Ecaterina 2, 040155, Bucharest, Romania.
- 13. Research Center for Integrated Analysis and Territorial Management, Faculty of Geography, University of Bucharest, 4-12 Regina Elisabeta Boulevard, 030018, Bucharest, Romania.; Faculty of Administration and Business, University of Bucharest, 4-12 Regina Elisabeta Boulevard, 030018, Bucharest, Romania
- 14. Department of Biomedical Engineering and Health Engineering Innovation Center, Khalifa University, 127788, Abu Dhabi, United Arab Emirates.
Description
Abstract
The complexity in the styles of 1200 Byzantine icons painted between 13th and 16th from Greece, Russia and Romania was investigated through the Kolmogorov algorithmic information theory. The aim was to identify specific quantitative patterns which define the key characteristics of the three different painting schools. Our novel approach using the artificial surface images generated with Inverse FFT and the Midpoint Displacement (MD) algorithms, was validated by comparison of results with eight fractal and non-fractal indices. From the analyzes performed, normalized Kolmogorov compression complexity (KC) proved to be the best solution because it had the best complexity pattern differentiations, is not sensitive to the image size and the least affected by noise. We conclude that normalized KC methodology does offer capability to differentiate the icons within a School and amongst the three Schools.
Notes
Files
Kolmogorov compression complexity.pdf
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Additional details
Related works
- Is identical to
- PMC9232591 (pmcid)
- https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9232591/pdf/41598_2022_Article_12826.pdf (URL)
- Is part of
- 2045-2322 (ISSN)
- Is supplemented by
- t https://doi.org/ 10.1038/s41598-022-12826-w (Handle)