A Novel Algorithm for Skeleton Extraction from Images Using Topological Graph Analysis

Liping Yang, Diane Oyen, Brendt Wohlberg

CVPRW 2019 pp. 1162-1166

doi:10.1109/CVPRW.2019.00152 /cvprw/2019/yang2019cvprw-novel/

Abstract

Skeletonization, also called thinning, is an important pre-processing step in computer vision and image processing tasks such as shape analysis and vectorization. It is a morphological process that generates a skeleton from an input image. Many thinning algorithms have been proposed, but accurate and fast algorithms are still in demand. In this paper, we propose a novel algorithm using embedded topological graphs and computational geometry that can extract skeletons from input binary images. We compare three well-known thinning algorithms with our method, with the experimental results showing effectiveness of the proposed method and algorithms.

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Cite

Text

Yang et al. "A Novel Algorithm for Skeleton Extraction from Images Using Topological Graph Analysis." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2019. doi:10.1109/CVPRW.2019.00152

Markdown

[Yang et al. "A Novel Algorithm for Skeleton Extraction from Images Using Topological Graph Analysis." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2019.](https://mlanthology.org/cvprw/2019/yang2019cvprw-novel/) doi:10.1109/CVPRW.2019.00152

BibTeX

@inproceedings{yang2019cvprw-novel,
  title     = {{A Novel Algorithm for Skeleton Extraction from Images Using Topological Graph Analysis}},
  author    = {Yang, Liping and Oyen, Diane and Wohlberg, Brendt},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2019},
  pages     = {1162-1166},
  doi       = {10.1109/CVPRW.2019.00152},
  url       = {https://mlanthology.org/cvprw/2019/yang2019cvprw-novel/}
}