DIGITAL PARTICLE IMAGE VELOCIMETRY CORRELATION ALGORITHM AT FOUCAULT-HILBERT DOMAINS - SLEZIAK, Mariusz (Trends in education, 2010)
The modern image acquisition and processing methods are widely used at scientific and industrial applications for solving of huge number of semantically different tasks. The general structures of information technologies used for decisions making processes (DMP) at these applications are, basically, similar including three fundamental stages: visualization, image analysis, identification procedural sets. The realization of these procedures determine mostly the operation quality of whole technological chain, semantic analysis and total effectiveness of DMP at systems. The recent developing of artificial intelligence and knowledge engineering theory based on conceptions of intelligent knowledge networks prove these thesis [1]. Otherwise, this emphasizes the importance of further developing and unification of low-level (physical, logical, systematic, networking layers) methods and procedural sets based on signal and image processing. The developed, during the second half of XX century, digital Fourier- and Hilbert-optics could be recognized as the informative and very effective methodology of modern information-measuring systems design [2,3]. The publications of this article's authors also consider the aspects of physical fields visualization, image analysis, segmentation (textures fragmentation) and identification of complex shape objects'(CSO) and textures' (CST) images as structural elements of dynamic scenes [4,5,6,7]. The continuation of such research activities, by authors' opinion, is well-founded and could provide the increasing of contextually instruments' quality.
Keywords: flow visualization; particle image velocimetry; Foucault-Hilbert method.