ML Anthology

2-D Digital Curve Analysis: A Regularity Measure

Bruno Vasselle, Gérard Giraudon
ICCV 1993 pp. 556-561
doi:10.1109/ICCV.1993.378162 /iccv/1993/vasselle1993iccv-d/

Abstract

A regularity measure for discrete line geometry is presented. This quantitative measure based on a ratio between line lengths at different scales is analyzed in the framework of Brownian motion theory. The measure at a given scale is always computed from the maximum precision image, so that it does not introduce any subresolution assumption. A scale choice determines the quantity of global information vs. local information to be measured. Its statistical behavior is studied on two extremal models of curves: the Brownian motion and the digitized straight line. It is shown that this quantitative measure leads to relevant shape information. To illustrate this fact, an image segmentation application example is discussed based essentially on geometry criteria of region boundaries. Some experimental results performed on real-scene images are presented.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

PDF ICCV Semantic Scholar

Cite

Text

Vasselle and Giraudon. "2-D Digital Curve Analysis: A Regularity Measure." IEEE/CVF International Conference on Computer Vision, 1993. doi:10.1109/ICCV.1993.378162

Markdown

[Vasselle and Giraudon. "2-D Digital Curve Analysis: A Regularity Measure." IEEE/CVF International Conference on Computer Vision, 1993.](https://mlanthology.org/iccv/1993/vasselle1993iccv-d/) doi:10.1109/ICCV.1993.378162

BibTeX

@inproceedings{vasselle1993iccv-d,
  title     = {{2-D Digital Curve Analysis: A Regularity Measure}},
  author    = {Vasselle, Bruno and Giraudon, Gérard},
  booktitle = {IEEE/CVF International Conference on Computer Vision},
  year      = {1993},
  pages     = {556-561},
  doi       = {10.1109/ICCV.1993.378162},
  url       = {https://mlanthology.org/iccv/1993/vasselle1993iccv-d/}
}