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Artificial Neural Networks and Fuzzy Logic for Specifying the Color of an Image Using Munsell Soil-Color Charts

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Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations (IPMU 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 853))

Abstract

The Munsell soil-color charts contain 238 standard color chips arranged in seven charts with Munsell notation. They are widely used to determine soil color by visual comparison, seeking the closest match between a soil sample and one of the chips. The Munsell designation of this chip (hue, value, and chroma) is assigned to the soil under study. However, the available chips represent only a subset of all possible soil colors, in which the visual appearance for an observer is usually intermediate between several chips. Our study proposes an intelligent system which combines two Soft Computing Techniques (Artificial Neural Networks and Fuzzy Logic Systems) aimed at finding a set of chips as similar as possible to a given soil sample. This is under the precondition that the soil sample is an image taken by a digital camera or mobile phone. The system receives an image as input and returns a set of color-chip designations as output.

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Abbreviations

ANN:

Artificial Neural Network

MCC:

Munsell Color Chart

FS:

Fuzzy System

HVC:

Hue, Value, and Chroma

MSE:

Mean Squared Error

RGB:

Red Green Blue

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Author information

Authors and Affiliations

  1. Department of Computer Science and Artificial Intelligence, University of Granada, c/Periodista Daniel Saucedo Aranda s.n., 18071, Granada, Spain

    María Carmen Pegalajar, Luis G. Baca Ruíz, Luis Mansilla & Miguel Delgado

  2. Department of Soil Science and Agricultural Chemistry, University of Granada, Campus Fuentenueva s.n., 18071, Granada, Spain

    Manuel Sánchez-Marañón

Authors
  1. María Carmen Pegalajar
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  2. Manuel Sánchez-Marañón
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  3. Luis G. Baca Ruíz
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  4. Luis Mansilla
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  5. Miguel Delgado
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Corresponding author

Correspondence to María Carmen Pegalajar .

Editor information

Editors and Affiliations

  1. Universidad de Cádiz, Cádiz, Cadiz, Spain

    Jesús Medina

  2. Universidad de Málaga, Málaga, Málaga, Spain

    Manuel Ojeda-Aciego

  3. Universidad de Granada, Granada, Spain

    José Luis Verdegay

  4. Universidad de Granada, Granada, Spain

    David A. Pelta

  5. Universidad de Málaga, Málaga, Málaga, Spain

    Inma P. Cabrera

  6. LIP6, Université Pierre et Marie Curie, CNRS, Paris, France

    Bernadette Bouchon-Meunier

  7. Iona College, New Rochelle, New York, USA

    Ronald R. Yager

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Pegalajar, M.C., Sánchez-Marañón, M., Baca Ruíz, L.G., Mansilla, L., Delgado, M. (2018). Artificial Neural Networks and Fuzzy Logic for Specifying the Color of an Image Using Munsell Soil-Color Charts. In: Medina, J., et al. Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations. IPMU 2018. Communications in Computer and Information Science, vol 853. Springer, Cham. https://doi.org/10.1007/978-3-319-91473-2_59

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  • DOI: https://doi.org/10.1007/978-3-319-91473-2_59

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-91472-5

  • Online ISBN: 978-3-319-91473-2

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