Title
Fast inline inspection by Neural Network Based Filtered Backprojection : application to apple inspection
Author
Faculty/Department
Faculty of Sciences. Physics
Publication type
article
Publication
Subject
Physics
Source (journal)
Case Studies in Nondestructive Testing and Evaluation
Volume/pages
6(2016) :B , p. 14-20
ISSN
22146571
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
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.
Full text (open access)
https://repository.uantwerpen.be/docman/irua/3db6c4/133359.pdf
Handle