Cellular neural network for real time image processing

G. Vagliasindi, P. Arena, L. Fortuna, G. Mazzitelli, A. Murari

Research output: Contribution to conferencePaper


Since their introduction in 1988, Cellular Nonlinear Networks (CNNs) have found a key role as image processing instruments. Thanks to their structure they are able of processing individual pixels in a parallel way providing fast image processing capabilities that has been applied to a wide range of field among which nuclear fusion. In the last years, indeed, visible and infrared video cameras have become more and more important in tokamak fusion experiments for the twofold aim of understanding the physics and monitoring the safety of the operation. Examining the output of these cameras in real-time can provide significant information for plasma control and safety of the machines. The potentiality of CNNs can be exploited to this aim. To demonstrate the feasibility of the approach, CNN image processing has been applied to several tasks both at the Frascati Tokamak Upgrade (FTU) and the Joint European Torus (JET). © 2008 American Institute of Physics.
Original languageEnglish
Publication statusPublished - 2008
Externally publishedYes
EventInternational Conference on Burning Plasma Diagnostics - , Italy
Duration: 1 Jan 2008 → …


ConferenceInternational Conference on Burning Plasma Diagnostics
Period1/1/08 → …


All Science Journal Classification (ASJC) codes

  • Physics and Astronomy(all)

Cite this

Vagliasindi, G., Arena, P., Fortuna, L., Mazzitelli, G., & Murari, A. (2008). Cellular neural network for real time image processing. Paper presented at International Conference on Burning Plasma Diagnostics, Italy. https://doi.org/10.1063/1.2905120