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On Region Merging: The Statistical Soundness of Fast Sorting, with Applications

Frank Nielsen, Richard Nock
CVPR 2003 pp. 19-26
doi:10.1109/CVPR.2003.1211447 /cvpr/2003/nielsen2003cvpr-region/

Abstract

This work explores a statistical basis for a process often described in computer vision: image segmentation by region merging following a particular order in the choice of regions. We exhibit a particular blend of algorithmics and statistics whose error is, as we formally show, close to the best possible. This approach can be approximated in a very fast segmentation algorithm for processing images described using most common numerical feature spaces. Simple modifications of the algorithm allow us to cope with occlusions and/or hard noise levels. Experiments on grey-level and color images, obtained with a short C-code, display the quality of the segmentations obtained.

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Cite

Text

Nielsen and Nock. "On Region Merging: The Statistical Soundness of Fast Sorting, with Applications." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2003. doi:10.1109/CVPR.2003.1211447

Markdown

[Nielsen and Nock. "On Region Merging: The Statistical Soundness of Fast Sorting, with Applications." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2003.](https://mlanthology.org/cvpr/2003/nielsen2003cvpr-region/) doi:10.1109/CVPR.2003.1211447

BibTeX

@inproceedings{nielsen2003cvpr-region,
  title     = {{On Region Merging: The Statistical Soundness of Fast Sorting, with Applications}},
  author    = {Nielsen, Frank and Nock, Richard},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2003},
  pages     = {19-26},
  doi       = {10.1109/CVPR.2003.1211447},
  url       = {https://mlanthology.org/cvpr/2003/nielsen2003cvpr-region/}
}