ML Anthology

Finding Junctions Using the Image Gradient

David James Beymer
CVPR 1991 pp. 720-721
doi:10.1109/CVPR.1991.139798 /cvpr/1991/beymer1991cvpr-finding/

Abstract

The author proposes a junction detector that works by filling in gaps at junctions in edge maps. It uses the image gradient to guide extensions of disconnected edges at junctions. A novel representation for the gradient, the bow tie map, is used to implement the endpoint growing rules, which include following gradient ridges and using saddle points in the gradient magnitude. The authors demonstrate the junction detector on real imagery.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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Cite

Text

Beymer. "Finding Junctions Using the Image Gradient." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1991. doi:10.1109/CVPR.1991.139798

Markdown

[Beymer. "Finding Junctions Using the Image Gradient." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1991.](https://mlanthology.org/cvpr/1991/beymer1991cvpr-finding/) doi:10.1109/CVPR.1991.139798

BibTeX

@inproceedings{beymer1991cvpr-finding,
  title     = {{Finding Junctions Using the Image Gradient}},
  author    = {Beymer, David James},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1991},
  pages     = {720-721},
  doi       = {10.1109/CVPR.1991.139798},
  url       = {https://mlanthology.org/cvpr/1991/beymer1991cvpr-finding/}
}