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17 February 2020 Classification using a three-dimensional sensor in a structured industrial environment
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Usage of a three-dimensional (3-D) sensor and point clouds provides various benefits over the usage of a traditional camera for industrial inspection. We focus on the development of a classification solution for industrial inspection purposes using point clouds as an input. The developed approach employs deep learning to classify point clouds, acquired via a 3-D sensor, the final goal being to verify the presence of certain industrial elements in the scene. We possess the computer-aided design model of the whole mechanical assembly and an in-house developed localization module provides initial pose estimation from which 3-D point clouds of the elements are inferred. The accuracy of this approach is proved to be acceptable for industrial usage. Robustness of the classification module in relation to the accuracy of the localization algorithm is also estimated.

© 2020 SPIE and IS&T 1017-9909/2020/$28.00 © 2020 SPIE and IS&T
Ivan Mikhailov, Igor Jovancevic, Nour Islam Mokhtari, and Jean-José Orteu "Classification using a three-dimensional sensor in a structured industrial environment," Journal of Electronic Imaging 29(4), 041008 (17 February 2020).
Received: 1 October 2019; Accepted: 9 January 2020; Published: 17 February 2020


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