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Scandinavian Conference on Image Analysis

SCIA 2019: Image Analysis pp 128–139Cite as

Zonohedral Approximation of Spherical Structuring Element for Volumetric Morphology

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Part of the Lecture Notes in Computer Science book series (LNIP,volume 11482)

Abstract

Performing dilation and erosion using large structuring elements can be computationally slow – a problem especially pronounced when processing volumetric data. To reduce the computational complexity of dilation/erosion using spherical structuring elements, we propose a method for approximating a sphere with a zonohedron. Since zonohedra can be created via successive dilations/erosions of line segments, this allows morphological operations to be performed in constant time per voxel. As the complexity of commonly used methods typically scales with the size of the structuring element, our method significantly improves the run time. We use the proposed approximation to detect large spherical objects in volumetric data. Results are compared with other image analysis frameworks demonstrating constant run time and significant performance gains.

Keywords

  • Morphology
  • Computational efficiency
  • Zonohedra

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Author information

Authors and Affiliations

  1. Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, Denmark

    Patrick M. Jensen, Camilla H. Trinderup, Anders B. Dahl & Vedrana A. Dahl

Authors
  1. Patrick M. Jensen
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  2. Camilla H. Trinderup
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  3. Anders B. Dahl
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  4. Vedrana A. Dahl
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Corresponding author

Correspondence to Patrick M. Jensen .

Editor information

Editors and Affiliations

  1. Linköping University, Linköping, Sweden

    Prof. Dr. Michael Felsberg

  2. Linköping University, Linköping, Sweden

    Per-Erik Forssén

  3. Uppsala University, Uppsala, Sweden

    Dr. Ida-Maria Sintorn

  4. Linköping University, Linköping, Sweden

    Prof. Dr. Jonas Unger

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Jensen, P.M., Trinderup, C.H., Dahl, A.B., Dahl, V.A. (2019). Zonohedral Approximation of Spherical Structuring Element for Volumetric Morphology. In: Felsberg, M., Forssén, PE., Sintorn, IM., Unger, J. (eds) Image Analysis. SCIA 2019. Lecture Notes in Computer Science(), vol 11482. Springer, Cham. https://doi.org/10.1007/978-3-030-20205-7_11

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  • DOI: https://doi.org/10.1007/978-3-030-20205-7_11

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