ML Anthology

Adaptive Active Contour Algorithms for Extracting and Mapping Thick Curves

Christos Davatzikos, Jerry L. Prince
CVPR 1993 pp. 524-529
doi:10.1109/CVPR.1993.341080 /cvpr/1993/davatzikos1993cvpr-adaptive/

Abstract

Two new adaptive active contour algorithms for the extraction and mapping of the skeleton of a thick curve are described. They are based on conditions which guarantee uniqueness and fidelity of the solution. Both algorithms modify the regularization constant K/sub o/ in an attempt to maintain convexity of the energy function while simultaneously improving the fidelity of the result. The first algorithm changes K/sub o/ over time while the second adapts K/sub o/ spatially. Both algorithms are evaluated on experiments with synthetic curves; both demonstrate an improved performance compared to a fixed-parameter active contour algorithm.< <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

Davatzikos and Prince. "Adaptive Active Contour Algorithms for Extracting and Mapping Thick Curves." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1993. doi:10.1109/CVPR.1993.341080

Markdown

[Davatzikos and Prince. "Adaptive Active Contour Algorithms for Extracting and Mapping Thick Curves." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1993.](https://mlanthology.org/cvpr/1993/davatzikos1993cvpr-adaptive/) doi:10.1109/CVPR.1993.341080

BibTeX

@inproceedings{davatzikos1993cvpr-adaptive,
  title     = {{Adaptive Active Contour Algorithms for Extracting and Mapping Thick Curves}},
  author    = {Davatzikos, Christos and Prince, Jerry L.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1993},
  pages     = {524-529},
  doi       = {10.1109/CVPR.1993.341080},
  url       = {https://mlanthology.org/cvpr/1993/davatzikos1993cvpr-adaptive/}
}