This paper presents a very high-speed image processing algorithm applied to multi-faceted asymmetric radiation from the edge (MARFE) detection on the Joint European Torus. The algorithm was built in serial and parallel versions and written in C/C+ using OpenCV, cvBlob, and LibSVM libraries. The code implemented was characterized by its accuracy and run-time performance. The final result of the parallel version achieves a correct detection rate of 97.6% for MARFE identification and an image processing rate of more than 10 000 frame per second. The parallel version divides the image processing chain into two groups and seven tasks. One group is responsible for Background Image Estimation and Image Binarization modules, and the other is responsible for region Feature Extraction and Pattern Classification. At the same time and to maximize the workload distribution, the parallel code uses data parallelism and pipeline strategies for these two groups, respectively. A master thread is responsible for opening, signaling, and transferring images between both groups. The algorithm has been tested in a dedicated Intel symmetric-multiprocessing computer architecture with a Linux operating system.

A 10000-Image-per-Second Parallel Algorithm for Real-Time Detection of MARFEs on JET

Andrea Murari;
2013

Abstract

This paper presents a very high-speed image processing algorithm applied to multi-faceted asymmetric radiation from the edge (MARFE) detection on the Joint European Torus. The algorithm was built in serial and parallel versions and written in C/C+ using OpenCV, cvBlob, and LibSVM libraries. The code implemented was characterized by its accuracy and run-time performance. The final result of the parallel version achieves a correct detection rate of 97.6% for MARFE identification and an image processing rate of more than 10 000 frame per second. The parallel version divides the image processing chain into two groups and seven tasks. One group is responsible for Background Image Estimation and Image Binarization modules, and the other is responsible for region Feature Extraction and Pattern Classification. At the same time and to maximize the workload distribution, the parallel code uses data parallelism and pipeline strategies for these two groups, respectively. A master thread is responsible for opening, signaling, and transferring images between both groups. The algorithm has been tested in a dedicated Intel symmetric-multiprocessing computer architecture with a Linux operating system.
2013
Istituto gas ionizzati - IGI - Sede Padova
Inglese
41
2
341
349
9
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6423951
Sì, ma tipo non specificato
Image processing
multi-faceted asymmetric radiation from the edge detection
multi-faceted asymmetric radiation from the edge identification
parallel algorithm
This work has been carried out under the European Fusion Development Agreement under the Brazil-The European Atomic Energy Community collaboration agreement on fusion research, coordinated by the Brazilian Fusion Network and by the Brazilian Nuclear Energy Commission. "Funding under Association Contract FU07-CT-2007-00053"./ Article number: 6423951 / La rivista è pubblicata anche online con ISSN 1939-9375.
6
info:eu-repo/semantics/article
262
Portes de Albuquerque, Márcio; Murari, Andrea; Giovani, M; Alves Jr, Nilton; Portes de Albuquerque, Marcelo; Contributors, Jetefda
01 Contributo su Rivista::01.01 Articolo in rivista
none
   EU Fusion for ITER Applications
   EUFORIA
   FP7
   211804
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/181811
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 2
social impact