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Extension of a One-Dimensional Convexity Measure to Two Dimensions

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Combinatorial Image Analysis (IWCIA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10256))

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Abstract

In this paper we propose a new idea to design a measure for shape descriptors based on the concept of Q-convexity. The new measure extends the directional convexity measure defined in [2] to a two-dimensional convexity measure. The derived shape descriptors have the following features: (1) their values range from 0 to 1; (2) their values equal 1 if and only if the binary image is Q-convex; (3) they are invariant by reflection and point symmetry; (4) their computation can be easily and efficiently implemented.

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Acknowledgements

The collaboration of the authors was supported by the COST Action MP1207 “EXTREMA: Enhanced X-ray Tomographic Reconstruction: Experiment, Modeling, and Algorithms”. The research of Péter Balázs and Péter Bodnár was supported by the NKFIH OTKA [grant number K112998]. The authors also thank the anonymous reviewers for their useful observations which enhanced the quality of the paper.

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Authors and Affiliations

  1. Dipartimento di Ingegneria dell’Informazione e Scienze Matematiche, Via Roma, 56, 53100, Siena, Italy

    Sara Brunetti

  2. Department of Image Processing and Computer Graphics, University of Szeged, Árpád tér 2., Szeged, 6720, Hungary

    Péter Balázs & Péter Bodnár

Authors
  1. Sara Brunetti
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  2. Péter Balázs
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  3. Péter Bodnár
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Corresponding author

Correspondence to Péter Balázs .

Editor information

Editors and Affiliations

  1. SUNY Buffalo State, Buffalo, New York, USA

    Valentin E. Brimkov

  2. Department of Applied Professional Studies, SUNY Fredonia, Fredonia, New York, USA

    Reneta P. Barneva

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Brunetti, S., Balázs, P., Bodnár, P. (2017). Extension of a One-Dimensional Convexity Measure to Two Dimensions. In: Brimkov, V., Barneva, R. (eds) Combinatorial Image Analysis. IWCIA 2017. Lecture Notes in Computer Science(), vol 10256. Springer, Cham. https://doi.org/10.1007/978-3-319-59108-7_9

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  • DOI: https://doi.org/10.1007/978-3-319-59108-7_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59107-0

  • Online ISBN: 978-3-319-59108-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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