A template matching approach based on the discrepancy norm for defect detection on regularly textured surfaces
|Titel||A template matching approach based on the discrepancy norm for defect detection on regularly textured surfaces|
|Buchtitel||Proceedings of the 10th International Conference on Quality Control by Artificial Vision (QCAV'2011)|
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 behaviour like monotonicity and a Lipschitz property. The proposed approach relies only on few parameters which make 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.