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Fuzzy Techniques in Image Processing : Three Case Studies

Mike Nachtegael, Dietrich Van der Weken and Etienne E. Kerre

p. 89-104

    Abstract

    Fuzzy techniques can be applied in several domains of image processing (Kerre & Nachtegael, 2000). In this paper we will show how fuzzy techniques are used in mathematical morphology, in establishing measures for image quality evaluation, and in constructing filters for image noise reduction

    Index

    Keywords

    image processing, morphology, filters, noise reduction, similarity measures

    Text

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    References

    Bibliographical reference

    Mike Nachtegael, Dietrich Van der Weken and Etienne E. Kerre, « Fuzzy Techniques in Image Processing : Three Case Studies », CASYS, 12 | 2002, 89-104.

    Electronic reference

    Mike Nachtegael, Dietrich Van der Weken and Etienne E. Kerre, « Fuzzy Techniques in Image Processing : Three Case Studies », CASYS [Online], 12 | 2002, Online since 16 July 2024, connection on 27 December 2024. URL : http://popups.uliege.be/3041-539x/index.php?id=1686

    Authors

    Mike Nachtegael

    Department of Applied Mathematics and Computer Science, Fuzziness and Uncertainty Modelling Research Unit, Ghent University, Krijgslaan 281 (Building S9), 9000, Gent, Belgium.

    Dietrich Van der Weken

    Department of Applied Mathematics and Computer Science, Fuzziness and Uncertainty Modelling Research Unit, Ghent University, Krijgslaan 281 (Building S9), 9000, Gent, Belgium.

    Etienne E. Kerre

    Department of Applied Mathematics and Computer Science, Fuzziness and Uncertainty Modelling Research Unit, Ghent University, Krijgslaan 281 (Building S9), 9000, Gent, Belgium.

    By this author

    Copyright

    CC BY-SA 4.0 Deed