Surface defects inspection of cold rolled strips based on neural network

Defects on the surface of steel strips are main factors to evaluate quality of steel strips, surface inspection is of great importance to improve quality of steel strips. Traditional surface inspection by human inspectors is far from satisfactory. In this paper, an approach to detect surface defects...

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Bibliographic Details
Published in2005 International Conference on Machine Learning and Cybernetics Vol. 8; pp. 5034 - 5037 Vol. 8
Main Authors Ge-Wen Kang, Hong-Bing Liu
Format Conference Proceeding
LanguageEnglish
Japanese
Published IEEE 2005
Subjects
Cold rolled strips
Defect detection
Feature extraction
Feedforward neural networks
Feedforward systems
Frequency
Gabor filters
Humans
Image processing
Inspection
Machine vision
Neural network
Neural networks
Steel
Strips
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ISBN0780390911
9780780390911
ISSN2160-133X
DOI10.1109/ICMLC.2005.1527830

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Summary:Defects on the surface of steel strips are main factors to evaluate quality of steel strips, surface inspection is of great importance to improve quality of steel strips. Traditional surface inspection by human inspectors is far from satisfactory. In this paper, an approach to detect surface defects of steel strips based on feed-forward neural network (FFN) is discussed. The experiments show that the method is effective.
ISBN:0780390911
9780780390911
ISSN:2160-133X
DOI:10.1109/ICMLC.2005.1527830