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Proceedings Paper

High-performance surface inspection method for thin-film sensors
Author(s): Volkmar Wieser; Stefan Larndorfer; Bernhard Moser
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Paper Abstract

Thin-film sensors for use in automotive or aeronautic applications must conform to very high quality standards. Due to defects that cannot be addressed by conventional electronic measurements, an accurate optical inspection is imperative to ensure long-term quality aspects of the produced thin-film sensor. In this particular case, resolutions of 1 &mgr;m per pixel are necessary to meet the required high quality standards. Furthermore, it has to be guaranteed that defects are detected robustly with high reliability. In this paper, a new method is proposed that solves the problem of handling local deformations due to production variabilities without having to use computational intensive local image registration operations. The main idea of this method is based on a combination of efficient morphological preprocessing and a multi-step comparison strategy based on logical implication. The main advantage of this approach is that the neighborhood operations that care for the robustness of the image comparison can be computed in advance and stored in a modified reference image. By virtue of this approach, no further neighborhood operations have to be carried out on the acquired test image during inspection time. A systematic, experimental study shows that this method is superior to existing approaches concerning reliability, robustness, and computational efficiency. As a result, the requirements of high-resolution inspection and high-performance throughput while accounting for local deformations are met very well by the implemented inspection system. The work is substantiated with theoretical arguments and a comprehensive analysis of the obtained performance and practical usability in the above-mentioned, challenging industrial environment.

Paper Details

Date Published: 28 February 2007
PDF: 11 pages
Proc. SPIE 6503, Machine Vision Applications in Industrial Inspection XV, 65030A (28 February 2007); doi: 10.1117/12.703561
Show Author Affiliations
Volkmar Wieser, Software Competence Ctr. GmbH (Austria)
Stefan Larndorfer, Software Competence Ctr. GmbH (Austria)
Bernhard Moser, Software Competence Ctr. GmbH (Austria)

Published in SPIE Proceedings Vol. 6503:
Machine Vision Applications in Industrial Inspection XV
Fabrice Meriaudeau; Kurt S. Niel, Editor(s)

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