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Image Feature Extraction Using OD-Monotone Functions

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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))

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Abstract

Edge detection is a basic technique used as a preliminary step for, e.g., object extraction and recognition in image processing. Many of the methods for edge detection can be fit in the breakdown structure by Bezdek, in which one of the key parts is feature extraction. This work presents a method to extract edge features from a grayscale image using the so-called ordered directionally monotone functions. For this purpose we introduce some concepts about directional monotonicity and present two construction methods for feature extraction operators. The proposed technique is competitive with the existing methods in the literature. Furthermore, if we combine the features obtained by different methods using penalty functions, the results are equal or better results than state-of-the-art methods.

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Acknowledgments

This work is supported by the Spanish Ministry of Science (Project TIN2016-77356-P) and the Research Services of Universidad Publica de Navarra.

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Authors and Affiliations

  1. Dpto. Automatica y Computacion, Universidad Publica de Navarra, Campus Arrosadia, 31006, Pamplona, Spain

    Cedric Marco-Detchart, Carlos Lopez-Molina, Javier Fernández, Miguel Pagola & Humberto Bustince

  2. Institute of Smart Cities, Universidad Publica de Navarra, Campus Arrosadia, 31006, Pamplona, Spain

    Cedric Marco-Detchart, Javier Fernández, Miguel Pagola & Humberto Bustince

Authors
  1. Cedric Marco-Detchart
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  2. Carlos Lopez-Molina
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  3. Javier Fernández
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  4. Miguel Pagola
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  5. Humberto Bustince
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Corresponding author

Correspondence to Cedric Marco-Detchart .

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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Marco-Detchart, C., Lopez-Molina, C., Fernández, J., Pagola, M., Bustince, H. (2018). Image Feature Extraction Using OD-Monotone Functions. 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_23

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  • DOI: https://doi.org/10.1007/978-3-319-91473-2_23

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  • Online ISBN: 978-3-319-91473-2

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