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Proceedings Paper

A template matching approach based on the discrepancy norm for defect detection on regularly textured surfaces
Author(s): Jean-Luc Bouchot; Gernot Stübl; Bernhard Moser
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Paper Abstract

In this paper we introduce a novel algorithm for automatic fault detection in textures. We study the problem of finding a defect in regularly textured images with an approach based on a template matching principle. We aim at registering patches of an input image in a defect-free reference sample according to some admissible transformations. This approach becomes feasible by introducing the so-called discrepancy norm as fitness function which shows particular behavior like a monotonicity and a Lipschitz property. The proposed approach relies only on few parameters which makes it an easily adaptable algorithm for industrial applications and, above all, it avoids complex tuning of configuration parameters. Experiments demonstrate the feasibility and the reliability of the proposed algorithms with textures from real-world applications in the context of quality inspection of woven textiles.

Paper Details

Date Published: 12 July 2011
PDF: 10 pages
Proc. SPIE 8000, Tenth International Conference on Quality Control by Artificial Vision, 80000K (12 July 2011); doi: 10.1117/12.889865
Show Author Affiliations
Jean-Luc Bouchot, Johannes Kepler Univ. Linz (Austria)
Gernot Stübl, Software Competence Ctr. Hagenberg (Austria)
Bernhard Moser, Software Competence Ctr. Hagenberg (Austria)

Published in SPIE Proceedings Vol. 8000:
Tenth International Conference on Quality Control by Artificial Vision
Jean-Charles Pinoli; Johan Debayle; Yann Gavet; Frédéric Gruy; Claude Lambert, Editor(s)

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