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Mayor-Torrens t-norms in the Fuzzy Mathematical Morphology and Their Applications

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Fuzzy Logic and Information Fusion

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 339))

Abstract

Fuzzy mathematical morphology has been extensively used in many different applications such as edge detection, noise reduction and shape and pattern recognition. The fundamentals of this morphology are based on an appropriate selection of the operators involved, namely the conjunction and implication. In this work we investigate the use of the Mayor-Torrens family of t-norms, from both theoretical and practical point of view. The results suggest that competitive results can be obtained by using the t-norms of this family.

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Notes

  1. 1.

    It can be downloaded from ftp://figment.csee.usf.edu/pub/ROC/edge_comparison_dataset.tar.gz.

  2. 2.

    This image database can be downloaded from http://sipi.usc.edu/database/misc.tar.gz.

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Acknowledgments

This project was partially supported by the Spanish project TIN 2013-42795-P. P. Bibiloni also benefited from a fellowship of the Conselleria d’Educaci, Cultura i Universitats of the Govern de les Illes Balears under an operational program co-financed by the European Social Fund.

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Authors and Affiliations

  1. Department of Mathematics and Computer Science, University of the Balearic Islands, Palma, Spain

    P. Bibiloni, M. González-Hidalgo, S. Massanet, A. Mir & D. Ruiz-Aguilera

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  1. P. Bibiloni
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  2. M. González-Hidalgo
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  3. S. Massanet
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  4. A. Mir
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  5. D. Ruiz-Aguilera
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Corresponding author

Correspondence to M. González-Hidalgo .

Editor information

Editors and Affiliations

  1. University of Alcalá, Alcalá de Henares, Spain

    Tomasa Calvo Sánchez

  2. University of Balearic Islands, Palma, Spain

    Joan Torrens Sastre

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Bibiloni, P., González-Hidalgo, M., Massanet, S., Mir, A., Ruiz-Aguilera, D. (2016). Mayor-Torrens t-norms in the Fuzzy Mathematical Morphology and Their Applications. In: Calvo Sánchez, T., Torrens Sastre, J. (eds) Fuzzy Logic and Information Fusion. Studies in Fuzziness and Soft Computing, vol 339. Springer, Cham. https://doi.org/10.1007/978-3-319-30421-2_13

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  • DOI: https://doi.org/10.1007/978-3-319-30421-2_13

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  • Online ISBN: 978-3-319-30421-2

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