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http://dx.doi.org/10.14372/IEMEK.2022.17.6.337

Multi-Vision-based Inspection of Mask Ear Loops Attachment in Mask Production Lines  

JiMyeong, Woo (Department of IT Convergence Engineering, Kumoh National Institute of Technology)
SangHyeon, Lee (Department of IT Convergence Engineering, Kumoh National Institute of Technology)
Heoncheol, Lee (Department of IT Convergence Engineering, Kumoh National Institute of Technology)
Publication Information
IEMEK Journal of Embedded Systems and Applications / v.17, no.6, 2022 , pp. 337-346 More about this Journal
Abstract
This paper addresses the problem of vision-based ear loops ansd attachment inspection in mask production lines. This paper focuses on connections with ear loops and mask filter by an efficient combined approach. The proposed method used a template matching, shape detection and summation of histogram with preprocessing. We had a parameter for detecting defects heuristically. If the shape vertices are lower than the parameters our proposed method will find defective mask automatically. After finding normal masks in mask ear loops attachment status inspection algorithm our proposed method conducts attachment amount inspection. Our experimental results showed that the precision is 1 and the recall is 0.99 in the mask attachment status inspection and attachment amount inspection.
Keywords
Multi-vision-based inspection; Image processing; Manufacturing automation;
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Times Cited By KSCI : 2  (Citation Analysis)
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