A novel aircraft wing inspection framework based on multiple view geometry and convolutional neural network

Simple item page
dc.contributor.authorKuang, Boyu
dc.contributor.authorRana, Zeeshan
dc.contributor.authorZhao, Yifan
dc.date.accessioned2021-03-26T14:15:30Z
dc.date.available2021-03-26T14:15:30Z
dc.date.issued2020-02-28
dc.description.abstractTo achieve greener and safer aeronautical operations, this paper considers the problem of reconstructing the three-dimensional (3D) geometric structure of aeronautical components. A novel framework that recovers the 3D shapes by means of convolutional neural network (ConvNets) and multiple view geometry (MVG) operating on Mask-R-CNN-segmented two-dimensional images is proposed. To achieve more accurate 3D aircraft’s surface and exclude the invalid background structures, this paper innovatively integrates the environmental robustness of ConvNets and geometric adaptation of Mask-R- CNN into the MVG theory. The preliminary experiments show that the proposed framework is visual-comfortable, and it also accurately reconstructs the regions with damage to catch up with the inspection purpose.en_UK
dc.identifier.citationKuang B, Rana Z, Zhao Y. (2020) A novel aircraft wing inspection framework based on multiple view geometry and convolutional neural network. In: Aerospace Europe Conference 2020 (AEC2020), Bordeaux, France, 25-28 February 2020en_UK
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/16512
dc.language.isoenen_UK
dc.publisherCouncil of European Aerospace Societies (CEAS)en_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectsurface inspectionen_UK
dc.subjectgreener and safer aviationen_UK
dc.subjectdeep learningen_UK
dc.subjectimage segmentationen_UK
dc.subjectpoint clouden_UK
dc.titleA novel aircraft wing inspection framework based on multiple view geometry and convolutional neural networken_UK
dc.typeConference paperen_UK

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
A_novel_aircraft_wing_inspection_framework-2020.pdf
Size:
1.87 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.63 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Staff publications (SATM)