In magnetic confinement Nuclear Fusion video cameras have become routine diagnostics, which can produce gigabytes of data per discharge. New tools and methods are required to manipulate the frames of these videos to obtain the required information. New algorithms have been developed, which implement pattern recognition methods to search the repositories of videos on the basis of their content and not on their address. Real time automatic analysis of videos has motivated the development of machine learning tools to classify objects in images. The identification and tracking of objects in the videos of Tokamak diagnostics requires the computation of image descriptors, which are insensitive to rotation, translation and rescaling. The Hu moments have proved to be quite effective in performing this image analysis task. © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
All Science Journal Classification (ASJC) codes
- Condensed Matter Physics