Detection of small or low-contrast defects on web inspection

Jyrki Laitinen

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

2 Citations (Scopus)

Abstract

In many web inspection applications the inspection should be able to detect and classify a large number of different- sized defects with varying scattering properties. As a consequence, a high-resolution system with a wide dynamic range is needed. The performance of the system should also remain uniform over the image area. Three major elements affecting the image formation of a web inspection system are illumination, imaging and detection algorithms. The relationship between these elements and the final image quality is discussed. Practical examples of how the system performance is related to the quality of the image formation are given. In the examples small or low-contrast defect samples picked from industrial manufacturing process are analyzed. Defects are classified as small if they cover an area of ten CCD pixels or less in the image plane or they have such an orientation that the size of the defect in one dimension is extremely small as is in the case of some scratches. The defect is considered as low-contrast if the relative defect contrast is less than the pattern noise in the imaging system. As a conclusion some criteria and an approach for the systematization of the design of the image formation are discussed.
Original languageEnglish
Title of host publicationMachine Vision Applications in Industrial Inspection VI
EditorsA. Ravishankar Rao, Ning S. Chang
Place of PublicationBellingham
PublisherInternational Society for Optics and Photonics SPIE
Pages68-79
ISBN (Print)978-0-8194-2746-5
DOIs
Publication statusPublished - 1998
MoE publication typeA4 Article in a conference publication
EventMachine Vision Applications in Industrial Inspection VI - San Jose, United States
Duration: 24 Jan 199830 Jan 1998

Publication series

SeriesProceedings of SPIE
Volume3306
ISSN0277-786X

Conference

ConferenceMachine Vision Applications in Industrial Inspection VI
Country/TerritoryUnited States
CitySan Jose
Period24/01/9830/01/98

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