NDLI: On improving performance of surface inspection systems by online active learning and flexible classifier updates

Content Provider	Springer Nature Link
Author	Weigl, Eva Heidl, Wolfgang Lughofer, Edwin Radauer, Thomas Eitzinger, Christian
Copyright Year	2015
Abstract	Classification of detected events is a central component in state-of-the-art surface inspection systems that still relies on manual parametrization. While machine-learned classifiers promise supreme accuracy, their reliability depends on complete and correct annotation of an extensive training database, leaving the risk of unpredictable behavior in changing production environments. We propose an active learning-based training framework, which selectively presents questionable events for user annotation and is capable of online operation. Evaluation results on two data streams from microfluidic chips and elevator sheaves production show that annotation effort can be reduced by 90 % with negligible loss of accuracy. Simulation runs introducing new event classes show that the online active learning procedure is both efficient in terms of learning speed and robust in maintaining the accuracy levels of existing classes. The results underline the feasibility and potential of our approach that significantly reduces the required effort for inspection system setup and adapts to changes in the production process.
Starting Page	103
Ending Page	127
Page Count	25
File Format	PDF
ISSN	09328092
Journal	Machine Vision and Applications
Volume Number	27
Issue Number	1
e-ISSN	14321769
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2015-11-20
Publisher Place	Berlin/Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Visual quality inspection Image-based classification of event types Dynamic classifier updates Active learning Pattern Recognition Image Processing and Computer Vision Communications Engineering, Networks
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Computer Science Applications Software Hardware and Architecture

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