Kolmogorov compression complexity may differentiate different schools of Orthodox iconography
Daniel Peptenatu, Ion Andronache, Helmut Ahammer, R. P. Taylor, Ioannis Liritzis, Marko Radulović, Bogdan Ciobanu, Marin Burcea, Matjaž Perc, Tuan D. Pham, Bojan Tomić, Cosmin Iulian CÎRSTEA, Adrian Nicolae Lemeni, Andreea Karina Gruia, Alexandra Grecu, Marian Marin, Herbert F. Jelinek
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.