Publication
Title
Fast inline inspection by Neural Network Based Filtered Backprojection : application to apple inspection
Author
Abstract
Speed is an important parameter of an inspection system. Inline computed tomography systems exist but are generally expensive. Moreover, their throughput is limited by the speed of the reconstruction algorithm. In this work, we propose a Neural Network-based Hilbert transform Filtered Backprojection (NN-hFBP) method to reconstruct objects in an inline scanning environment in a fast and accurate way. Experiments based on apple X-ray scans show that the NN-hFBP method allows to reconstruct images with a substantially better tradeoff between image quality and reconstruction time.
Language
English
Source (journal)
Case Studies in Nondestructive Testing and Evaluation
Publication
2016
ISSN
22146571
DOI
10.1016/J.CSNDT.2016.03.003
Volume/pages
6 :B (2016) , p. 14-20
Full text (Publisher's DOI)
Full text (open access)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Record
Identifier
Creation 12.05.2016
Last edited 07.10.2022
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