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Authors: Mohammed Arshad Siddiqui 1 and Vitaliy Kurlin 2

Affiliations: 1 PDPM Indian Institute of Information Technology Design and Manufacturing, Jabalpur, India ; 2 University of Liverpool, U.K.

Keyword(s): Edge Detection, Thinning, Skeletonization, Polygonal Mesh.

Abstract: Microscopic images of vortex fields are important for understanding phase transitions in superconductors. These optical images include noise with high and variable intensity, hence are manually processed to extract numerical data from underlying meshes. The current thinning and skeletonization algorithms struggle to find connected meshes in these noisy images and often output edge pixels with numerous gaps and superfluous branching point. We have developed a new symmetric thinning algorithms to extract from such highly noisy images 1-pixel wide skeletons with theoretical guarantees. The resulting skeleton is converted into a polygonal mesh that has only polygonal edges at sub-pixel resolution. The experiments on over 100 real and 6250 synthetic images establish the state-of-the-art in extracting optimal meshes from highly noisy images.

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Paper citation in several formats:
Siddiqui, M. and Kurlin, V. (2020). Polygonal Meshes of Highly Noisy Images based on a New Symmetric Thinning Algorithm with Theoretical Guarantees. In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP; ISBN 978-989-758-402-2; ISSN 2184-4321, SciTePress, pages 137-146. DOI: 10.5220/0009340301370146

@conference{visapp20,
author={Mohammed Arshad Siddiqui. and Vitaliy Kurlin.},
title={Polygonal Meshes of Highly Noisy Images based on a New Symmetric Thinning Algorithm with Theoretical Guarantees},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP},
year={2020},
pages={137-146},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009340301370146},
isbn={978-989-758-402-2},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP
TI - Polygonal Meshes of Highly Noisy Images based on a New Symmetric Thinning Algorithm with Theoretical Guarantees
SN - 978-989-758-402-2
IS - 2184-4321
AU - Siddiqui, M.
AU - Kurlin, V.
PY - 2020
SP - 137
EP - 146
DO - 10.5220/0009340301370146
PB - SciTePress

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