Kolmogorov compression complexity may differentiate different schools of Orthodox iconography

Daniel Peptenatu; Ion Andronache; Helmut Ahammer; Richard Taylor; Ioannis Liritzis; Marko Radulovic; Bogdan Ciobanu; Marin Burcea; Matjaz Perc; Tuan D. Pham; Bojan M. Tomić; Cosmin Iulian Cîrstea; Adrian Nicolae Lemeni; Andreea Karina Gruia; Alexandra Grecu; Marian Marin; Herbert Franz Jelinek

doi:10.1038/s41598-022-12826-w

Kolmogorov compression complexity may differentiate different schools of Orthodox iconography

Daniel Peptenatu, Ion Andronache, Helmut Ahammer, Richard Taylor, Ioannis Liritzis, Marko Radulovic, Bogdan Ciobanu, Marin Burcea, Matjaz Perc, Tuan D. Pham, Bojan M. Tomić, Cosmin Iulian Cîrstea, Adrian Nicolae Lemeni, Andreea Karina Gruia, Alexandra Grecu, Marian Marin, Herbert Franz Jelinek

Biomedical Engineering & Biotechnology

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

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.

Original language	British English
Article number	10743
Journal	Scientific Reports
Volume	12
Issue number	1
DOIs	https://doi.org/10.1038/s41598-022-12826-w
State	Published - Dec 2022

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Peptenatu, D., Andronache, I., Ahammer, H., Taylor, R., Liritzis, I., Radulovic, M., Ciobanu, B., Burcea, M., Perc, M., Pham, T. D., Tomić, B. M., Cîrstea, C. I., Lemeni, A. N., Gruia, A. K., Grecu, A., Marin, M., & Jelinek, H. F. (2022). Kolmogorov compression complexity may differentiate different schools of Orthodox iconography. Scientific Reports, 12(1), Article 10743. https://doi.org/10.1038/s41598-022-12826-w

@article{ffb1ded7117f45c0a2956aefb7cf3969,

title = "Kolmogorov compression complexity may differentiate different schools of Orthodox iconography",

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.",

author = "Daniel Peptenatu and Ion Andronache and Helmut Ahammer and Richard Taylor and Ioannis Liritzis and Marko Radulovic and Bogdan Ciobanu and Marin Burcea and Matjaz Perc and Pham, {Tuan D.} and Tomi{\'c}, {Bojan M.} and C{\^i}rstea, {Cosmin Iulian} and Lemeni, {Adrian Nicolae} and Gruia, {Andreea Karina} and Alexandra Grecu and Marian Marin and Jelinek, {Herbert Franz}",

note = "Funding Information: The research was conducted by the Research Center for Integrated Analysis and Territorial Management-CAIMT, Faculty of Geography, University of Bucharest. The research was supported by a grant of the Romanian Ministry of Education and Research, CNCS—UEFISCDI, project number PN-III-P4-ID-PCE-2020-1076, within PNCDI III, grant of the Ministry of Research, Innovation and Digitization, CNCS/CCCDI-UEFISCDI, project number PN-III-P2-2.1-SOL-2021-0084, within PNCDI III and two grants of the University of Bucharest, Romania, project number 10680 UB and 10681 UB. M.P. was supported by the Slovenian Research Agency (Grant Nos. P1-0403 and J1-2457). I.L. is thankful for support of Sino-Hellenic Academic Project ( www.huaxiahellas.com ) from Key Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization of Henan Province, Henan University, Kaifeng, China. B.M.T. was supported by the Ministry of Education, Science and Technological Development of the Republic of Serbia (Contract No. 451-03-68/2020-14/200053). The authors like to acknowledge Jade Sterling for reviewing the paper and helpful suggestions. Publisher Copyright: {\textcopyright} 2022, The Author(s).",

year = "2022",

month = dec,

doi = "10.1038/s41598-022-12826-w",

language = "British English",

volume = "12",

journal = "Scientific Reports",

issn = "2045-2322",

publisher = "Nature Publishing Group",

number = "1",

}

Peptenatu, D, Andronache, I, Ahammer, H, Taylor, R, Liritzis, I, Radulovic, M, Ciobanu, B, Burcea, M, Perc, M, Pham, TD, Tomić, BM, Cîrstea, CI, Lemeni, AN, Gruia, AK, Grecu, A, Marin, M & Jelinek, HF 2022, 'Kolmogorov compression complexity may differentiate different schools of Orthodox iconography', Scientific Reports, vol. 12, no. 1, 10743. https://doi.org/10.1038/s41598-022-12826-w

TY - JOUR

T1 - Kolmogorov compression complexity may differentiate different schools of Orthodox iconography

AU - Peptenatu, Daniel

AU - Andronache, Ion

AU - Ahammer, Helmut

AU - Taylor, Richard

AU - Liritzis, Ioannis

AU - Radulovic, Marko

AU - Ciobanu, Bogdan

AU - Burcea, Marin

AU - Perc, Matjaz

AU - Pham, Tuan D.

AU - Tomić, Bojan M.

AU - Cîrstea, Cosmin Iulian

AU - Lemeni, Adrian Nicolae

AU - Gruia, Andreea Karina

AU - Grecu, Alexandra

AU - Marin, Marian

AU - Jelinek, Herbert Franz

N1 - Funding Information: The research was conducted by the Research Center for Integrated Analysis and Territorial Management-CAIMT, Faculty of Geography, University of Bucharest. The research was supported by a grant of the Romanian Ministry of Education and Research, CNCS—UEFISCDI, project number PN-III-P4-ID-PCE-2020-1076, within PNCDI III, grant of the Ministry of Research, Innovation and Digitization, CNCS/CCCDI-UEFISCDI, project number PN-III-P2-2.1-SOL-2021-0084, within PNCDI III and two grants of the University of Bucharest, Romania, project number 10680 UB and 10681 UB. M.P. was supported by the Slovenian Research Agency (Grant Nos. P1-0403 and J1-2457). I.L. is thankful for support of Sino-Hellenic Academic Project ( www.huaxiahellas.com ) from Key Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization of Henan Province, Henan University, Kaifeng, China. B.M.T. was supported by the Ministry of Education, Science and Technological Development of the Republic of Serbia (Contract No. 451-03-68/2020-14/200053). The authors like to acknowledge Jade Sterling for reviewing the paper and helpful suggestions. Publisher Copyright: © 2022, The Author(s).

PY - 2022/12

Y1 - 2022/12

N2 - 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.

AB - 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.

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U2 - 10.1038/s41598-022-12826-w

DO - 10.1038/s41598-022-12826-w

M3 - Article

C2 - 35750777

AN - SCOPUS:85132914226

SN - 2045-2322

VL - 12

JO - Scientific Reports

JF - Scientific Reports

IS - 1

M1 - 10743

ER -

Kolmogorov compression complexity may differentiate different schools of Orthodox iconography

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