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UAV-based Inspection of Airplane Exterior Screws with Computer Vision

Julien Miranda 1 Stanislas Larnier 2 Ariane Herbulot 1 Michel Devy 1
1 LAAS-RAP - Équipe Robotique, Action et Perception
LAAS - Laboratoire d'analyse et d'architecture des systèmes
Abstract : We propose a new approach to detect and inspect aircraft exterior screws. An Unmanned Aerial Vehicle (UAV) locating itself in the aircraft frame thanks to lidar technology is able to acquire precise images coming with useful metadata. We use a method based on a convolutional neural network (CNN) to characterize zones of interest (ZOI) and to extract screws from images; methods are proposed to create prior model for matching. Classic matching approaches are used to match the screws from this model with the detected ones, to increase screw recognition accuracy and detect missing screws, giving the system a new ability. Computer vision algorithms are then applied to evaluate the state of each visible screw, and detect missing and loose ones.
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Contributor : Julien Miranda <>
Submitted on : Wednesday, March 13, 2019 - 4:31:45 PM
Last modification on : Thursday, June 10, 2021 - 3:01:30 AM
Long-term archiving on: : Friday, June 14, 2019 - 12:24:01 PM


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  • HAL Id : hal-02065284, version 1


Julien Miranda, Stanislas Larnier, Ariane Herbulot, Michel Devy. UAV-based Inspection of Airplane Exterior Screws with Computer Vision. 14h International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications., Feb 2019, Prague, Czech Republic. ⟨hal-02065284⟩



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