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Image Triangulation Using the Sobel Operator for Vertex Selection (Media Exposition)

Authors Olivia X. Laske, Lori Ziegelmeier

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Subject Classification

ACM Subject Classification
  • Computing methodologies → Image processing
Keywords
  • Image Triangulation
  • Sharpening
  • Sobel Edge Detection
  • Delaunay Triangulation

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Abstract

Image triangulation, the practice of decomposing images into triangles, deliberately employs simplification to create an abstracted representation. While triangulating an image is a relatively simple process, difficulties arise when determining which vertices produce recognizable and visually pleasing output images. With the goal of producing art, we discuss an image triangulation algorithm in Python that utilizes Sobel edge detection and point cloud sparsification to determine final vertices for a triangulation, resulting in the creation of artistic triangulated compositions.

Cite As Get BibTex

Olivia X. Laske and Lori Ziegelmeier. Image Triangulation Using the Sobel Operator for Vertex Selection (Media Exposition). In 40th International Symposium on Computational Geometry (SoCG 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 293, pp. 91:1-91:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024) https://doi.org/10.4230/LIPIcs.SoCG.2024.91

Author Details

Olivia X. Laske
  • Department of Mathematics, Statistics, and Computer Science, Macalester College, St. Paul, MN, USA
Lori Ziegelmeier
  • Department of Mathematics, Statistics, and Computer Science, Macalester College, St. Paul, MN, USA

Funding

  • Ziegelmeier, Lori: Support through NSF:CDS&E-MSS-1854703 and NSF:BCS-2318171.

Supplementary Materials

References

  1. Olivia X. Laske and Lori Ziegelmeier. OliviaLaske/ImageTriangulation. Software, swhId: https://archive.softwareheritage.org/swh:1:dir:9ffab16fab1c54439e4641ae8167740d984993b8;origin=https://github.com/OliviaLaske/ImageTriangulation;visit=swh:1:snp:19a7dc185c4ffd416a264dcdbf1d71344ea48620;anchor=swh:1:rev:f3593de856785f90f66d888f62678400851ba223, (visited on 21/05/2024). URL: https://github.com/OliviaLaske/ImageTriangulation.
  2. Laske, Olivia. Source code, Image Triangulation. https://github.com/OliviaLaske/ImageTriangulation, 2024. Accessed March 2024.
  3. Kai Lawonn and Tobias Günther. Stylized image triangulation. Computer Graphics Forum, 38(1):221-234, 2019. URL: https://onlinelibrary.wiley.com/doi/pdf/10.1111/cgf.13526.
  4. David Marwood, Pascal Massimino, Michele Covell, and Shumeet Baluja. Representing images in 200 bytes: Compression via triangulation, 2018. URL: https://arxiv.org/abs/1809.02257.
  5. Godwin Onoja and Terhemen Aboiyar. Digital image segmentation using delaunay triangulation algorithm. Nigerian Annals of Pure and Applied Sciences, 3:268-283, July 2020. URL: https://doi.org/10.46912/napas.83.
  6. Tuan D. Pham. Kriging-weighted laplacian kernels for grayscale image sharpening. IEEE Access, 10:57094-57106, 2022. URL: https://doi.org/10.1109/ACCESS.2022.3178607.
  7. Simo, Endre. Delaunay Image Triangulation. https://www.esimov.com/2019/04/image-triangulation-in-go, 2019. Accessed March 2024.
  8. Run Tian, Guiling Sun, Xiaochao Liu, and Bowen Zheng. Sobel edge detection based on weighted nuclear norm minimization image denoising. Electronics, 10:655, March 2021. URL: https://doi.org/10.3390/electronics10060655.
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