A Confidence Measure for Boundary Detection and Object Selection

Mortensen, Eric N.; Barrett, William A.

doi:10.1109/CVPR.2001.990513

A Confidence Measure for Boundary Detection and Object Selection

Eric N. Mortensen, William A. Barrett

CVPR 2001 pp. I:477-484

doi:10.1109/CVPR.2001.990513 /cvpr/2001/mortensen2001cvpr-confidence/

Abstract

We introduce a confidence measure that estimates the assurance that a graph arc (or edge) corresponds to an object boundary in an image. A weighted, planar graph is imposed onto the watershed lines of a gradient magnitude image and the confidence measure is a function of the cost of fixed-length paths emanating from and extending to each end of a graph arc. The confidence measure is applied to automate the detection of object boundaries and thereby reduces (often greatly) the time and effort required for object boundary definition within a user-guided image segmentation environment.

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Cite

Text

Mortensen and Barrett. "A Confidence Measure for Boundary Detection and Object Selection." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2001. doi:10.1109/CVPR.2001.990513

Markdown

[Mortensen and Barrett. "A Confidence Measure for Boundary Detection and Object Selection." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2001.](https://mlanthology.org/cvpr/2001/mortensen2001cvpr-confidence/) doi:10.1109/CVPR.2001.990513

BibTeX

@inproceedings{mortensen2001cvpr-confidence,
  title     = {{A Confidence Measure for Boundary Detection and Object Selection}},
  author    = {Mortensen, Eric N. and Barrett, William A.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2001},
  pages     = {I:477-484},
  doi       = {10.1109/CVPR.2001.990513},
  url       = {https://mlanthology.org/cvpr/2001/mortensen2001cvpr-confidence/}
}