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Type II Fuzzy Image Segmentation

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Fuzzy Sets and Their Extensions: Representation, Aggregation and Models

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 220))

Abstract

Type II fuzzy sets are high-level representation of vague data with, compared to ordinary fuzzy sets, greater capability for uncertainty management. Theoretical aspects of type II fuzzy systems have been extensively investigated, and the research is still ongoing. Many image processing tasks accompanied with different types of imperfection. In this chapter, the applications of type II fuzzy sets for image segmentation will be discussed. Global and spatial type II segmentation schemes will be systematically introduced and examples will be provided.

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Authors
  1. Hamid R. Tizhoosh
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Editors and Affiliations

  1. Department of Automatics and Computation, Universidad Pública de Navarra, Campus Arrosadia s/n, 31006 Pamplona, Spain

    Humberto Bustince

  2. Department of Computer Science and Artificial Intelligence (DECSAI), University of Granada, Periodista Daniel Saucedo Aranda s/n, 18071 Granada, Spain

    Francisco Herrera

  3. Faculty of Mathematics, Universidad Complutense, Plaza de las Ciencias 3, 28040 Madrid, Spain

    Javier Montero

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Tizhoosh, H.R. (2008). Type II Fuzzy Image Segmentation. In: Bustince, H., Herrera, F., Montero, J. (eds) Fuzzy Sets and Their Extensions: Representation, Aggregation and Models. Studies in Fuzziness and Soft Computing, vol 220. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73723-0_31

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  • DOI: https://doi.org/10.1007/978-3-540-73723-0_31

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73722-3

  • Online ISBN: 978-3-540-73723-0

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