Deep learning-supported machine vision-based hybrid system combining inhomogeneous 2D and 3D data for the identification of surface defects

Deep learning-supported machine vision-based hybrid system combining inhomogeneous 2D and 3D data for the identification of surface defects

Machine vision systems for automatic defect detection commonly adopt 2D image-based systems or 3D laser triangulation systems. 2D and 3D systems present opposite advantages and disadvantages depending on the typology and position of defects to be detected. When the variety of defects is large, none...

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Bibliographic Details
Main Authors: Giorgio Cavaliere, Oswald Lanz, Yuri Borgianni, Enrico Savio
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Production and Manufacturing Research: An Open Access Journal
Subjects:
Surface defects analysis
hybrid 2D and 3D system
machine vision systems
deep learning
high-pressure die-casting
Online Access:https://www.tandfonline.com/doi/10.1080/21693277.2024.2378199
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https://www.tandfonline.com/doi/10.1080/21693277.2024.2378199

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