ML Anthology

Multi-Dimensional Robust Edge Detection

Linnan Liu, Brian G. Schunck, Charles R. Meyer
CVPR 1991 pp. 698-699
doi:10.1109/CVPR.1991.139787 /cvpr/1991/liu1991cvpr-multi/

Abstract

A multidimensional edge model is established and a first-order estimation for multidimensional edge profiles is proposed. An optimal edge location detection algorithm is developed. The advantages of the algorithm are that (1) it has little dependence on assumptions of edge models, noise models, or smoothing filters, (2) it has better abilities for detecting very weak edges and making less edge orientation errors than other edge detectors, (3) it can handle corners and complicated multidimensional image structures, and (4) it detects different edge types at the same time.< <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

Liu et al. "Multi-Dimensional Robust Edge Detection." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1991. doi:10.1109/CVPR.1991.139787

Markdown

[Liu et al. "Multi-Dimensional Robust Edge Detection." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1991.](https://mlanthology.org/cvpr/1991/liu1991cvpr-multi/) doi:10.1109/CVPR.1991.139787

BibTeX

@inproceedings{liu1991cvpr-multi,
  title     = {{Multi-Dimensional Robust Edge Detection}},
  author    = {Liu, Linnan and Schunck, Brian G. and Meyer, Charles R.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1991},
  pages     = {698-699},
  doi       = {10.1109/CVPR.1991.139787},
  url       = {https://mlanthology.org/cvpr/1991/liu1991cvpr-multi/}
}