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Fast Marching Based Superpixels Generation

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Mathematical Morphology and Its Applications to Signal and Image Processing (ISMM 2019)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11564))

Abstract

In this article, we present a fast-marching based algorithm for generating superpixel (FMS) partitions of images. The idea behind the algorithm is to draw an analogy between waves propagating in an heterogeneous medium and regions growing on an image at a rate depending on the local color and texture. The FMS algorithm is evaluated on the Berkeley Segmentation Dataset 500. It yields results in term of boundary adherence that are comparable to the ones obtained with state of the art algorithms including SLIC or ERGC, while improving on these algorithms in terms of compactness and density.

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Authors and Affiliations

  1. Centre for Mathematical Morphology, Mines ParisTech, PSL Research University, 35 rue Saint-Honoré, 77300, Fontainebleau, France

    Kaiwen Chang & Bruno Figliuzzi

Authors
  1. Kaiwen Chang
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  2. Bruno Figliuzzi
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Corresponding author

Correspondence to Bruno Figliuzzi .

Editor information

Editors and Affiliations

  1. Universität des Saarlandes, Saarbrücken, Germany

    Bernhard Burgeth

  2. Forschungszentrum Jülich GmbH, Jülich, Germany

    Andreas Kleefeld

  3. Université de Strasbourg, Illkirch Cedex, France

    Benoît Naegel

  4. Université de Reims Champagne-Ardenne, Reims Cedex 2, France

    Nicolas Passat

  5. Université Paris-Est, Noisy le Grand Cedex, France

    Benjamin Perret

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Chang, K., Figliuzzi, B. (2019). Fast Marching Based Superpixels Generation. In: Burgeth, B., Kleefeld, A., Naegel, B., Passat, N., Perret, B. (eds) Mathematical Morphology and Its Applications to Signal and Image Processing. ISMM 2019. Lecture Notes in Computer Science(), vol 11564. Springer, Cham. https://doi.org/10.1007/978-3-030-20867-7_27

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  • DOI: https://doi.org/10.1007/978-3-030-20867-7_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-20866-0

  • Online ISBN: 978-3-030-20867-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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