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An Application of Fuzzy Mathematical Morphology to Interval-Valued Knowledge Representation: A Remark

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Reliable Computing

Abstract

Mathematical morphology is known by its useful tools for processing binary (black-and-white) and gray-tone images. Due to the success of mathematical morphology in processing binary images, there have been many successful attempts to generalize its methods to more general, i.e. gray-tone images. One of these attempts—the most intuitive one is based on replacing sets by fuzzy sets, thus defining so called fuzzy morphological operations. In this paper we show that these operations can be used successfully in nonimage applications. We can use methods developed in fuzzy mathematical morphology to compute the membership functions of different "approximate" statements. Also, an application to interval-valued knowledge representation is given.

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Authors and Affiliations

  1. Department of Electrical Engineering, Texas A&M University, College Station, TX, 77843-3128, USA, e-mail

    Antony T. Popov

  2. Department of Mathematical Sciences, New Mexico State University, Las Cruces, NM, 88003, USA, e-mail

    Hung T. Nguyen

  3. Victoria University of Technology, MMC Melbourne, VIC, 8001, Australia, e-mail

    Leonid K. Reznik

Authors
  1. Antony T. Popov
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  2. Hung T. Nguyen
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  3. Leonid K. Reznik
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Popov, A.T., Nguyen, H.T. & Reznik, L.K. An Application of Fuzzy Mathematical Morphology to Interval-Valued Knowledge Representation: A Remark. Reliable Computing 4, 283–290 (1998). https://doi.org/10.1023/A:1009907730159

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