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Particle Swarm Optimization Of Fuzzy Penalty For 3D Image Reconstruction In X-Ray Tomography

Abstract : Engineers last year's works only on the 2D image data, to perceive defects in the CT images. This was a handicap facing the challenge of determining the 3D exact defect form. This paper presents a method for 3D image reconstruction, the most interesting in non destructive testing (NDT) especially due to its application in industrial imaging. We propose a new combined approach using particle swarm optimization (PSO) and fuzzy inference penalty, which will be helpful to elevate the hard inverse problem of 3D computed tomography.
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https://hal-uphf.archives-ouvertes.fr/hal-03418642
Contributor : Mylène Delrue Connect in order to contact the contributor
Submitted on : Monday, November 8, 2021 - 8:32:22 AM
Last modification on : Tuesday, November 9, 2021 - 4:05:13 AM

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  • HAL Id : hal-03418642, version 1

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Mohamed Tahar Ali Gouicem, Mostepha Yahi, Abdelmalik Taleb-Ahmed, Redouane Drai. Particle Swarm Optimization Of Fuzzy Penalty For 3D Image Reconstruction In X-Ray Tomography. International Conference on Welding, Non Destructive Testing and Materials and Alloys Industry (IC-WNDT-MI’14), Nov 2014, Annaba, Algeria. ⟨hal-03418642⟩

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