Edge Recognition in Dynamic Vision

McIvor, Alan M.

doi:10.1109/CVPR.1989.37838

Edge Recognition in Dynamic Vision

Alan M. McIvor

CVPR 1989 pp. 118-123

doi:10.1109/CVPR.1989.37838 /cvpr/1989/mcivor1989cvpr-edge/

Abstract

Using a model of an edge's motion through a sequence of images, the problem of its localization can be formulated as a stochastic filtering problem. The extended Kalman filter for such a system is considered in detail and is shown to be interpretable as a sequence of oriented special convolutions. Results are presented which show that the edge localization obtained using this filter is substantially better than that obtained using either the Sobel or Canny edge operators on each image individually.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>

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Cite

Text

McIvor. "Edge Recognition in Dynamic Vision." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1989. doi:10.1109/CVPR.1989.37838

Markdown

[McIvor. "Edge Recognition in Dynamic Vision." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1989.](https://mlanthology.org/cvpr/1989/mcivor1989cvpr-edge/) doi:10.1109/CVPR.1989.37838

BibTeX

@inproceedings{mcivor1989cvpr-edge,
  title     = {{Edge Recognition in Dynamic Vision}},
  author    = {McIvor, Alan M.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1989},
  pages     = {118-123},
  doi       = {10.1109/CVPR.1989.37838},
  url       = {https://mlanthology.org/cvpr/1989/mcivor1989cvpr-edge/}
}