The Integration of Region and Edge-Based Segmentation

Abstract

An algorithm is presented that integrates segmentation maps using both region and edge segmentation maps as input. The result of integration is a region map in which each region is large and compact. The operation is efficient and independent of image sources as well as segmentation techniques. The proposed algorithm allows multiple input maps and applies user-selected weights on various information sources. The scope of integration is parametrically controlled for the desired spatial resolution. A maximum likelihood estimator provides initial solutions of edge positions and strengths from multiple inputs. An iterative procedure is then used to smooth the resultant edge patterns. The edge map is converted to a region map using closed edge contours if desired. Finally, regions are merged to ensure that every region has the required properties. Experimental results are demonstrated using various segmentation techniques and real data from laser radar and thermal sensors.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Cite

Text

Chu and Aggarwal. "The Integration of Region and Edge-Based Segmentation." IEEE/CVF International Conference on Computer Vision, 1990. doi:10.1109/ICCV.1990.139507

Markdown

[Chu and Aggarwal. "The Integration of Region and Edge-Based Segmentation." IEEE/CVF International Conference on Computer Vision, 1990.](https://mlanthology.org/iccv/1990/chu1990iccv-integration/) doi:10.1109/ICCV.1990.139507

BibTeX

@inproceedings{chu1990iccv-integration,
  title     = {{The Integration of Region and Edge-Based Segmentation}},
  author    = {Chu, Chen-Chau and Aggarwal, Jake K.},
  booktitle = {IEEE/CVF International Conference on Computer Vision},
  year      = {1990},
  pages     = {117-120},
  doi       = {10.1109/ICCV.1990.139507},
  url       = {https://mlanthology.org/iccv/1990/chu1990iccv-integration/}
}