0468480 20240103213313.320170106235959.9 85019149149 000406771301032 10.1109/ICPR.2016.7899797 6 s. P cav_un_epca*0467540978-1-5090-4846-5PiscatawayIEEE2016 Solar flare moments of histogram turning point cav_un_auth*0101203 Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing 50 Suk Tomáš UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0100099 Sluneční oddělení Department of Solar Physics Department of Solar Physics - Team 1 50 Šimberová Stanislava ASU-R Astronomický ústav AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2016/ZOI/suk-0468480.pdf cav_un_auth*0314467 GA15-16928S GA ČR We propose methodology for the analysis of active regions on the Sun. It is based on high-order statistical moments of image histogram, particularly on its skewness. The methodology includes a new technique to select regions with possible formation of the flare. We track these areas in the time video sequences to search for triggers -- turning point(s), when the pre-flare phase changes to the full developed event. The frequency analysis in the flare formation areas is based on Fourier analysis, Morlet wavelets, and principal component analysis. Results have been evaluated to achieve the periods of oscillations stimulating the flare origin. cav_un_auth*0340495 23rd International Conference on Pattern Recognition ICPR 2016 20161204 20161208 Cancún MX IN 2017 2 PO ASU-R BN RVO:67985815 RVO:67985556 http://hdl.handle.net/11104/0266438 1 S 3+4 Proceedings Paper Computer Science Artificial Intelligence 2016 85019149149 SCOPUS PUBMED 000406771301032 WOS cav_un_epca*0467540 Proceedings of the 23rd International Conference on Pattern Recognition (ICPR) 978-1-5090-4846-5 Piscataway IEEE 2016