Local Statistic Based Region Segmentation with Automatic Scale Selection
Abstract
Recently, new segmentation models based on local information have emerged. They combine local statistics of the regions along the contour (inside and outside) to drive the segmentation procedure. Since they are based on local decisions, these models are more robust to local variations of the regions of interest (contrast, noise, blur, ...). They nonetheless also introduce some new difficulties which are inherent to the fact of basing a global property (the segmentation) on pure local decisions. This papers explores some of those difficulties and proposes some possible corrections. Results on both 2D and 3D data are compared to those obtained without these corrections.
Cite
Text
Piovano and Papadopoulo. "Local Statistic Based Region Segmentation with Automatic Scale Selection." European Conference on Computer Vision, 2008. doi:10.1007/978-3-540-88688-4_36Markdown
[Piovano and Papadopoulo. "Local Statistic Based Region Segmentation with Automatic Scale Selection." European Conference on Computer Vision, 2008.](https://mlanthology.org/eccv/2008/piovano2008eccv-local/) doi:10.1007/978-3-540-88688-4_36BibTeX
@inproceedings{piovano2008eccv-local,
title = {{Local Statistic Based Region Segmentation with Automatic Scale Selection}},
author = {Piovano, Jérome and Papadopoulo, Théodore},
booktitle = {European Conference on Computer Vision},
year = {2008},
pages = {486-499},
doi = {10.1007/978-3-540-88688-4_36},
url = {https://mlanthology.org/eccv/2008/piovano2008eccv-local/}
}