Detection and classification of painting defects using deep learning

In the visual inspection, the quality assurance is difficult, because the dispersion occurs in the result by skill and fatigue degree of the inspector. Recently, a visual inspection method by image processing using deep learning has been proposed. When using deep learning, the dataset to be used is...

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Bibliographic Details
Published in2021 36th International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC) pp. 1 - 4
Main Authors Adachi, Kazune, Natori, Takahiro, Aikawa, Naoyuki
Format Conference Proceeding
LanguageEnglish
Published IEEE 27.06.2021
Subjects
Classification algorithms
Deep learning
Image processing
Inspection
Production facilities
Quality assurance
Visual inspection
Visualization
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Summary:In the visual inspection, the quality assurance is difficult, because the dispersion occurs in the result by skill and fatigue degree of the inspector. Recently, a visual inspection method by image processing using deep learning has been proposed. When using deep learning, the dataset to be used is important. In this paper, we describe a method for detecting painting defects using image processing, automatically generating data for deep learning, and using these data for classification using deep learning.
DOI:10.1109/ITC-CSCC52171.2021.9524736