Computer Aided Quality Control

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.

  1. J. Weickert:
    Anisotropic diffusion filters for image processing based quality control.
    A. Fasano, M. Primicerio (Eds.): Proc. Seventh European Conf. on Mathematics in Industry. Teubner, Stuttgart, 355-362, 1994.

  2. 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.), Mathematik - Schlüsseltechnologie für die Zukunft. Springer, Berlin, 449-462, 1997.

  3. J. Weickert:
    A model for the cloudiness of fabrics:
    H. Neunzert (Ed.): Progress in industrial mathematics at ECMI 94. Wiley-Teubner, Chichester, 258-265, 1996.

  4. J. Weickert,
    A real-time algorithm for assessing inhomogeneities in fabrics,
    Real-Time Imaging, Vol. 5, 15-22, 1999.

  5. 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.

  6. 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.

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