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http://dx.doi.org/10.7842/kigas.2015.19.2.45

Development of Visual Inspection Process Adapting Naive Bayes Classifiers  

Ryu, Sun-Joong (Dept. of Mechanical Engineering, Dongyang Mirae University)
Publication Information
Journal of the Korean Institute of Gas / v.19, no.2, 2015 , pp. 45-53 More about this Journal
Abstract
In order to improve the performance of the visual inspection process, in addition to existing automatic visual inspection machine and human inspectors have developed a new process configuration using a Naive Bayes classifier. By applying the classifier, defect leakage and human inspector's work amount could be improved at the same time. New classification method called AMPB was applied instead of conventional methods based on MAP classification. By experimental results using the filter product for camera modules, it was confirmed that it is possible to configure the process at the level of leakage ratio 1.14% and human inspector's work amount ratio 75.5%. It is significant that the result can be applied in such a wide range as gas leak detection which is the collaboration process between inspection machine and human inspector's
Keywords
visual inspection; Naive Bayes; classifier;
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