Abstract
This paper addresses the problem of quality inspection of regular textured surfaces as, e.g., encountered in industrial woven fabrics. The motivation for developing a novel approach is to utilize the template matching principle for defect detection in a way that does not need any particular statistical, structural or spectral features to be calculated during the checking phase. It is shown that in this context template matching becomes both feasible and effective by exploiting the so-called discrepancy measure as fitness function, leading to a defect detection method that shows advantages in terms of easy configuration and low maintenance efforts.
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Stübl, G., Bouchot, JL., Haslinger, P., Moser, B. (2012). Discrepancy Norm as Fitness Function for Defect Detection on Regularly Textured Surfaces. In: Pinz, A., Pock, T., Bischof, H., Leberl, F. (eds) Pattern Recognition. DAGM/OAGM 2012. Lecture Notes in Computer Science, vol 7476. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32717-9_43
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DOI: https://doi.org/10.1007/978-3-642-32717-9_43
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