A Robust Active Contour Model with Insensitive Parameters
Abstract
Active contours, known as snakes, have found wide application since their first introduction in 1987 by M. Kass, A. Witkin and D. Terzopoulos. However, one problem with the current models is that the performance depends on proper internal parameters and initial contour position, which, unfortunately, cannot be determined a priori. It is usually difficult to tune internal parameters and initial contour position. The problem results from the fact that the internal normal force at each point of a contour is also a function of contour shape. To solve this problem, the authors propose to compensate for this internal normal force so as to make it independent of shape. As a result the new model works robustly with no necessity for tuning internal parameters and can converge to high curvature points like corners.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Cite
Text
Xu et al. "A Robust Active Contour Model with Insensitive Parameters." IEEE/CVF International Conference on Computer Vision, 1993. doi:10.1109/ICCV.1993.378161Markdown
[Xu et al. "A Robust Active Contour Model with Insensitive Parameters." IEEE/CVF International Conference on Computer Vision, 1993.](https://mlanthology.org/iccv/1993/xu1993iccv-robust/) doi:10.1109/ICCV.1993.378161BibTeX
@inproceedings{xu1993iccv-robust,
title = {{A Robust Active Contour Model with Insensitive Parameters}},
author = {Xu, Gang and Segawa, Eigo and Tsuji, Saburo},
booktitle = {IEEE/CVF International Conference on Computer Vision},
year = {1993},
pages = {562-566},
doi = {10.1109/ICCV.1993.378161},
url = {https://mlanthology.org/iccv/1993/xu1993iccv-robust/}
}