Color Image Segmentation Using Markov Random Fields

Daily, Michael J.

doi:10.1109/CVPR.1989.37865

Color Image Segmentation Using Markov Random Fields

Michael J. Daily

CVPR 1989 pp. 304-312

doi:10.1109/CVPR.1989.37865 /cvpr/1989/daily1989cvpr-color/

Abstract

The use of Markov random fields (MRFs) in color image segmentation of natural outdoor scenes is discussed. MRFs provide an elegant means of specifying a local energy function which embodies the expected dependencies of neighboring pixels and includes both the prior and posterior probabilistic distributions. This local neighborhood-based specification of dependencies avoids ad hoc brittle methods using global image knowledge. A brief analysis of ongoing research in color differencing methods is presented, since they are central to the problem of color segmentation. The authors develop and compare the use of three different lattice structures for coupled MRFs with line and color processes based on squares, hexagons, and triangles, and also discusses current efforts in MRF parameter understanding.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>

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Cite

Text

Daily. "Color Image Segmentation Using Markov Random Fields." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1989. doi:10.1109/CVPR.1989.37865

Markdown

[Daily. "Color Image Segmentation Using Markov Random Fields." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1989.](https://mlanthology.org/cvpr/1989/daily1989cvpr-color/) doi:10.1109/CVPR.1989.37865

BibTeX

@inproceedings{daily1989cvpr-color,
  title     = {{Color Image Segmentation Using Markov Random Fields}},
  author    = {Daily, Michael J.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1989},
  pages     = {304-312},
  doi       = {10.1109/CVPR.1989.37865},
  url       = {https://mlanthology.org/cvpr/1989/daily1989cvpr-color/}
}