ML Anthology

Combining Region Splitting and Edge Detection Through Guided Delaunay Image Subdivision

Theo Gevers, Arnold W. M. Smeulders
CVPR 1997 pp. 1021-1026
doi:10.1109/CVPR.1997.609455 /cvpr/1997/gevers1997cvpr-combining/

Abstract

In this paper, an adaptive split-and-merge segmentation method is proposed. The splitting phase of the algorithm employs the incremental Delaunay triangulation competent of forming grid edges of arbitrary orientation, and position. The tessellation grid, defined by the Delaunay triangulation, is adjusted to the semantics of the image data by combining similarity and difference information among pixels. Experimental results on synthetic images show that the method is robust to different object edge orientations, partially weak object edges and very noisy homogeneous regions. Experiments on a real image indicate that the method yields good segmentation results even when there is a quadratic sloping of intensities particularly suited for segmenting natural scenes of man-made objects.

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Text

Gevers and Smeulders. "Combining Region Splitting and Edge Detection Through Guided Delaunay Image Subdivision." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1997. doi:10.1109/CVPR.1997.609455

Markdown

[Gevers and Smeulders. "Combining Region Splitting and Edge Detection Through Guided Delaunay Image Subdivision." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1997.](https://mlanthology.org/cvpr/1997/gevers1997cvpr-combining/) doi:10.1109/CVPR.1997.609455

BibTeX

@inproceedings{gevers1997cvpr-combining,
  title     = {{Combining Region Splitting and Edge Detection Through Guided Delaunay Image Subdivision}},
  author    = {Gevers, Theo and Smeulders, Arnold W. M.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1997},
  pages     = {1021-1026},
  doi       = {10.1109/CVPR.1997.609455},
  url       = {https://mlanthology.org/cvpr/1997/gevers1997cvpr-combining/}
}