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Image Segmentation by Hierarchical Layered Oriented Image Foresting Transform Subject to Closeness Constraints

  • Conference paper
Discrete Geometry and Mathematical Morphology (DGMM 2024)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14605))

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Abstract

In this work, we address the problem of image segmentation, subject to high-level constraints expected for the objects of interest. More specifically, we define closeness constraints to be used in conjunction with geometric constraints of inclusion in the Hierarchical Layered Oriented Image Foresting Transform (HLOIFT) algorithm. The proposed method can handle the segmentation of a hierarchy of objects with nested boundaries, each with its own expected boundary polarity constraint, making it possible to control the maximum distances (in a geodesic sense) between the successive nested boundaries. The method is demonstrated in the segmentation of nested objects in colored images with superior accuracy compared to its precursor methods and also when compared to some recent click-based methods.

Thanks to Conselho Nacional de Desenvolvimento Científico e Tecnológico – CNPq – (Grant 407242/2021-0, 313087/2021-0, 166631/2018-3), CAPES (88887.136422/2017-00), FAPESP (2014/12236-1, 2014/50937-1) and IPT (Institute for Technological Research).

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Notes

  1. 1.

    https://github.com/SamsungLabs/ritm_interactive_segmentation/blob/master.

  2. 2.

    https://segment-anything.com/.

  3. 3.

    https://github.com/pauloavmiranda/HLOIFT_CC.

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Authors and Affiliations

  1. Institute of Mathematics and Statistics, University of São Paulo, São Paulo, SP, Brazil

    Luiz Felipe Dolabela Santos, Felipe Augusto de Souza Kleine & Paulo André Vechiatto Miranda

  2. Researcher at the IPT - Institute for Technological Research of the State of São Paulo, São Paulo, Brazil

    Felipe Augusto de Souza Kleine

Authors
  1. Luiz Felipe Dolabela Santos
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  2. Felipe Augusto de Souza Kleine
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  3. Paulo André Vechiatto Miranda
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Correspondence to Paulo André Vechiatto Miranda .

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Editors and Affiliations

  1. University of Siena, Siena, Italy

    Sara Brunetti

  2. University of Firenze, Firenze, Italy

    Andrea Frosini

  3. University of Siena, Siena, Italy

    Simone Rinaldi

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Santos, L.F.D., de Souza Kleine, F.A., Miranda, P.A.V. (2024). Image Segmentation by Hierarchical Layered Oriented Image Foresting Transform Subject to Closeness Constraints. In: Brunetti, S., Frosini, A., Rinaldi, S. (eds) Discrete Geometry and Mathematical Morphology. DGMM 2024. Lecture Notes in Computer Science, vol 14605. Springer, Cham. https://doi.org/10.1007/978-3-031-57793-2_26

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  • DOI: https://doi.org/10.1007/978-3-031-57793-2_26

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-57792-5

  • Online ISBN: 978-3-031-57793-2

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