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An adaptive embedded architecture for real-time Particle Image Velocimetry algorithms

Abstract : Particle Image Velocimetry (PIV) is a method of im-aging and analysing fields of flows. The PIV tech-niques compute and display all the motion vectors of the field in a resulting image. Speeds more than thou-sand vectors per second can be required, each speed being environment-dependent. Essence of this work is to propose an adaptive FPGA-based system for real-time PIV algorithms. The proposed structure is ge-neric so that this unique structure can be re-used for any PIV applications that uses the cross-correlation technique. The major structure remains unchanged, adaptations only concern the number of processing operations. The required speed (corresponding to the number of vector per second) is obtained thanks to a parallel processing strategy. The image processing designer duplicates the processing modules to distrib-ute the operations. The result is a FPGA-based archi-tecture, which is easily adapted to algorithm specifica-tions without any hardware requirement. The design flow is fast and reliable.
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Contributor : Alain Aubert Connect in order to contact the contributor
Submitted on : Wednesday, July 23, 2008 - 4:03:03 PM
Last modification on : Saturday, June 25, 2022 - 7:25:08 PM
Long-term archiving on: : Friday, September 21, 2012 - 10:05:30 AM


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  • HAL Id : ujm-00124018, version 1
  • ARXIV : 0807.3732



Alain Aubert, Nathalie Bochard, Virginie Fresse. An adaptive embedded architecture for real-time Particle Image Velocimetry algorithms. 14th European Signal Processing Conference - EUSIPCO 2006, Sep 2006, Florence, Italy. pp.F6.1 R4. ⟨ujm-00124018⟩



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