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Color Mathematical Morphology Using a Fuzzy Color-Based Supervised Ordering

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Fuzzy Information Processing (NAFIPS 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 831))

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Abstract

Mathematical morphology is a theory with applications in image processing and analysis. In a supervised approach to mathematical morphology, pixel values are ranked according to sets of foreground and background elements specified a priori by the user. In this paper, we introduce a supervised fuzzy color-based approach to color mathematical morphology that provides an elegant alternative to the support vector machine-based approach developed by Velasco-Forero and Angulo. Briefly, color elements are ranked according to the degree of truth of the proposition “the considered color is a foreground color but it is not a background color” in the new supervised color morphological approach. Furthermore, the vagueness and uncertainty inherent to the description of colors by humans can be naturally incorporated in the new approach using the concept of fuzzy colors.

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Notes

  1. 1.

    The surface of a mapping h in the red-green plane is formally defined by the set \(\{(x,y,z):z=h(x,y,0),0 \le x \le 1, 0 \le y \le 1\}\).

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Acknowledgment

This work was supported in part by CNPq under grant no 310118/2017-4.

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Authors and Affiliations

  1. Department of Applied Mathematics, University of Campinas, Rua Sérgio Buarque de Holanda, 651, Campinas, SP, 130830-859, Brazil

    Mateus Sangalli & Marcos Eduardo Valle

Authors
  1. Mateus Sangalli
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  2. Marcos Eduardo Valle
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Corresponding author

Correspondence to Marcos Eduardo Valle .

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Editors and Affiliations

  1. Department of Teleinformatics Engineering, Federal University of Ceará, Fortaleza, Ceará, Brazil

    Guilherme A. Barreto

  2. Department of Statistics & Applied Mathematics, Federal University of Ceará, Fortaleza, Ceará, Brazil

    Ricardo Coelho

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Sangalli, M., Valle, M.E. (2018). Color Mathematical Morphology Using a Fuzzy Color-Based Supervised Ordering. In: Barreto, G., Coelho, R. (eds) Fuzzy Information Processing. NAFIPS 2018. Communications in Computer and Information Science, vol 831. Springer, Cham. https://doi.org/10.1007/978-3-319-95312-0_24

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  • DOI: https://doi.org/10.1007/978-3-319-95312-0_24

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  • Online ISBN: 978-3-319-95312-0

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