An application of rough set theory to defect detection of automotive glass

Seungkoo Lee and George Vachtsevanos

Mathematics and Computers in Simulation (MATCOM), 2002, vol. 60, issue 3, 225-231

Abstract: A technique based on rough set theory is investigated for identifying defects on a backlight (a rear window of a vehicle with a defrost circuit). Since replacement of defective backlights result in a significant financial loss, automobile manufacturers are trying to remove defective backlights during the manufacturing process. Therefore, an automated inspection system based on infrared (IR) imaging techniques has been developed to detect backlight defects such as missing lines or hotspots, where the most challenging task is identifying hotspots from their artifacts.

Keywords: Rough set theory; Automated inspection system; Feature selection; Rule generation; Automotive glass (search for similar items in EconPapers)
Date: 2002
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:60:y:2002:i:3:p:225-231

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