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Fuzzy Hit-or-Miss Transform Using Uninorms

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Modeling Decisions for Artificial Intelligence (MDAI 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11144))

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Abstract

The Hit-or-Miss transform (HMT) is a morphological operator which has been successfully used to identify shapes and patterns satisfying certain geometric restrictions in an image. Recently, a novel HMT operator, called the fuzzy morphological HMT, was introduced within the framework of the fuzzy mathematical morphology based on fuzzy conjunctions and fuzzy implication functions. Taking into account that the particular case of considering a t-norm as fuzzy conjunction and its residual implication as fuzzy implication functions has proved its potential in several applications, in this paper, the case when residual implications derived from uninorms and a general fuzzy conjunction, possibly a t-norm or the same uninorm, is deeply analysed. In particular, some theoretical results related to properties desirable for the applications are proved. Finally, some experimental results are presented showing the potential of this choice of operator to detect shapes and patterns in images.

This paper has been partially supported by the Spanish Grant TIN2016-75404-P, AEI/FEDER, UE. P. Bibiloni also benefited from the fellowship FPI/1645/2014 of the Conselleria d’Educació, 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 Soft Computing, Image Processing and Aggregation (SCOPIA) Research Group, University of the Balearic Islands, 07122, Palma de Mallorca, Spain

    Pedro Bibiloni, Manuel González-Hidalgo, Sebastia Massanet, Arnau Mir & Daniel Ruiz-Aguilera

  2. Balearic Islands Health Research Institute (IdISBa), 07010, Palma, Spain

    Pedro Bibiloni, Manuel González-Hidalgo, Sebastia Massanet, Arnau Mir & Daniel Ruiz-Aguilera

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  1. Pedro Bibiloni
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  2. Manuel González-Hidalgo
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  3. Sebastia Massanet
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  4. Arnau Mir
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  5. Daniel Ruiz-Aguilera
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Corresponding author

Correspondence to Sebastia Massanet .

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Editors and Affiliations

  1. Maynooth University, Maynooth, Ireland

    Vicenç Torra

  2. Department Management Science, Tamagawa University, Tokyo, Japan

    Yasuo Narukawa

  3. University of the Balearic Islands, Palma de Mallorca, Spain

    Isabel Aguiló

  4. University of the Balearic Islands, Palma de Mallorca, Baleares, Spain

    Manuel González-Hidalgo

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Bibiloni, P., González-Hidalgo, M., Massanet, S., Mir, A., Ruiz-Aguilera, D. (2018). Fuzzy Hit-or-Miss Transform Using Uninorms. In: Torra, V., Narukawa, Y., Aguiló, I., González-Hidalgo, M. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2018. Lecture Notes in Computer Science(), vol 11144. Springer, Cham. https://doi.org/10.1007/978-3-030-00202-2_9

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  • DOI: https://doi.org/10.1007/978-3-030-00202-2_9

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