A Level Line Selection Approach for Object Boundary Estimation
Abstract
An energy model based approach for estimating object boundaries is presented. We study a particular energy whose minimizer can be determined. The method estimates the unknown number of objects and draws object boundaries by selecting the "best" level lines computed from level sets of the original image. Unlike previous standard methods, the proposed method does not require iteration for minimizing the energy. In addition, our segmentation algorithm combines anisotropic diffusion based regularization with level line selection to extract smooth object boundaries. Experimental results on 2D biomedical and meteorological images are reported.
Cite
Text
Kervrann et al. "A Level Line Selection Approach for Object Boundary Estimation." IEEE/CVF International Conference on Computer Vision, 1999. doi:10.1109/ICCV.1999.790352Markdown
[Kervrann et al. "A Level Line Selection Approach for Object Boundary Estimation." IEEE/CVF International Conference on Computer Vision, 1999.](https://mlanthology.org/iccv/1999/kervrann1999iccv-level/) doi:10.1109/ICCV.1999.790352BibTeX
@inproceedings{kervrann1999iccv-level,
title = {{A Level Line Selection Approach for Object Boundary Estimation}},
author = {Kervrann, Charles and Hoebeke, Mark and Trubuil, Alain},
booktitle = {IEEE/CVF International Conference on Computer Vision},
year = {1999},
pages = {963-968},
doi = {10.1109/ICCV.1999.790352},
url = {https://mlanthology.org/iccv/1999/kervrann1999iccv-level/}
}