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Sequential graph-based extraction of curvilinear structures

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Abstract

In this paper, a new approach is proposed to extract an ordered sequence of curvilinear structures in images, capturing the largest and most influential paths first and then progressively extracting smaller paths until a prespecified size is reached. The results are demonstrated both quantitatively and qualitatively using synthetic and real-world images. The method is shown to outperform comparator methods for certain cases of noise, object class, and scale, while remaining fundamentally easier to use due to its low parameter requirement.

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Notes

  1. The software has been implemented in MATLAB and is made available at: https://github.com/ShuaaAlharbi/SGE.

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Acknowledgements

Shuaa S. Alharbi and Haifa F. Alhasson are supported by the Saudi Arabian Ministry of Higher Education Doctoral Scholarship and Qassim University in Saudi Arabia.

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Authors and Affiliations

  1. Department of Computer Science, Durham University, Durham, UK

    Shuaa S. Alharbi, Chris G. Willcocks, Philip T. G. Jackson, Haifa F. Alhasson & Boguslaw Obara

  2. Computer Collage, Qassim University, Buraydah, Kingdom of Saudi Arabia

    Shuaa S. Alharbi & Haifa F. Alhasson

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  1. Shuaa S. Alharbi
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  2. Chris G. Willcocks
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  3. Philip T. G. Jackson
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  4. Haifa F. Alhasson
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  5. Boguslaw Obara
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Correspondence to Boguslaw Obara.

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Alharbi, S.S., Willcocks, C.G., Jackson, P.T.G. et al. Sequential graph-based extraction of curvilinear structures. SIViP 13, 941–949 (2019). https://doi.org/10.1007/s11760-019-01431-6

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  • DOI: https://doi.org/10.1007/s11760-019-01431-6

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