Publication details
Conference Paper (international conference)
Analysis of Dynamic Processes by Statistical Moments of High Orders
,
: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, p. 33-40
: CIARP 2013, Iberoamerican Congress on Pattern Recognition /18./, (Havana, CU, 20.11.2013-23.11.2013)
: GAP103/11/1552, GA ČR
: statistical moments, frequency analysis, Fourier and wavelet transformations
: http://library.utia.cas.cz/separaty/2013/ZOI/suk-0399779.pdf
(eng): We present a new approach to image analysis in temporal sequence of images (data cube). Our method is based on high-order statistical moments (skewness and kurtosis) giving interesting information about a dynamic event in the temporal sequence. The moments enable precise determination of the ”turning points” in the temporal sequence of images. The moment’s curves are analyzed by continuous complex Morlet wavelet that leads to the description of quasi-periodic processes in the investigated event as a time sequence of local spectra. These local spectra are compared with Fourier spectrum. We experimentally illustrate the performance on the real data from astronomical observations.
: BN