Quality control in industrial production is a key factor for the success
of the products. In order to achieve uniform quality standards,
automisation using machine vision methods is becoming more and
more important. Often real-time requirements create algorithmic challenges.
Defect Detection in Wood Surfaces
In furniture production it is important to use veneer
of high quality at all visible surfaces. We have developed
anisotropic diffusion filters that allow to identify defects
by a simple thresholding step
Visualisation of Dominant Stripes in Nonwoven Farbics
Nonwoven fabrics appear in numerous applications, ranging from
baby napkins over clothing industry to the agricultural sector.
One quality parameter is given by the anisotropy caused by dominant
stripe-like structures. Such structures can be made visible by
suitably adapted anistropic diffusion processes
Multiscale Analysis of the Cloudiness of Nonwoven Fabrics
The cloudiness constitutes another crucial quality parameter for
nonwoven fabrics. It is a scale phenomenon. Therefore, we have developed
a tool for automatic quality assessment taking into account the
cloudiness at multiple scales. It involves specific pyramid decomposition
and allows real-time assessment of an entire production line with a
This algorithm has entered the commercial sofware product
MASC-VQC of the Fraunhofer Institute for Techno- and Economathematics.
Multiple View Inspection of Aluminium Die Castings
While classical automated multiple view inspection requires calibrated
cameras, we propose a novel method that can also cope with uncalibrated
images. It tracks defects of industrial objects along an image sequence.
The success of this strategy is demonstated by applying it to the
inspection of aluminium die castings .
Automated Defect Detection in Wine Bottlenecks
For the inspection of wine bottlenecks, a novel system is constructed
that uses an inner lighting source. Computer vision methods are applied
for tracking potential defects along an image sequence. The current
implementation of the system detects 87 percent true positives and
0 percent false positives .
Anisotropic diffusion filters for image processing based
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Mathematics in Industry. Teubner, Stuttgart, 355-362, 1994.
H. Neunzert, B. Claus, K. Rjasanowa, R. Rösch, J. Weickert,
Mathematische Werkzeuge in der Bildverarbeitung zur
Qualitätsbestimmung von Oberflächen.
K.-H. Hoffmann, W. Jäger, T. Lohmann, H. Schunck (Eds.),
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Springer, Berlin, 449-462, 1997.
A model for the cloudiness of fabrics:
H. Neunzert (Ed.): Progress in industrial mathematics at ECMI 94.
Wiley-Teubner, Chichester, 258-265, 1996.
A real-time algorithm for assessing inhomogeneities in fabrics,
Real-Time Imaging, Vol. 5, 15-22, 1999.
L. Pizarro, D. Mery, R. Delpiano, M. Carrasco:
Robust automated multiple view inspection
Pattern Analysis and Applications, Vol. 11, No. 1, 21-32, 2008.
Revised version of
Technical Report No. 192, Department of Mathematics, Saarland
University, Saarbrücken, Germany, April 2007.
M. Carrasco, L. Pizarro, D. Mery:
Image acquisition and automated inspection of wine bottlenecks by tracking
in multiple views.
Proc. of the 8th International Conference on Signal Processing, Computational
Geometry and Artificial Vision - ISCGAV 2008, pp. 82-89, August 2008.