A Framework for Multiple Snakes

Abstract

A framework for segmenting multiple objects in an image based on deformable contours is proposed. In this framework, multiple snakes are applied with a new kind of energy called the "group energy." The group energy is introduced to handle sharing of properties across multiple objects in the image. Our framework allows contours of "strong objects" to guide contours of "weak objects" by utilizing deformable templates. We also automatically generate the necessary weighting parameters for energy minimization. A new approach for multiple snake optimization which is based on dynamic programming is also proposed. We applied our framework to the problem of image analysis of gene expression in microarrays. Comprehensive experiments were performed and comparisons were made between the individual energy based method and the proposed group energy based method. Our results are highly encouraging and have many potential applications in a variety of tracking scenarios.

Cite

Text

Srinark and Kambhamettu. "A Framework for Multiple Snakes." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2001. doi:10.1109/CVPR.2001.990960

Markdown

[Srinark and Kambhamettu. "A Framework for Multiple Snakes." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2001.](https://mlanthology.org/cvpr/2001/srinark2001cvpr-framework/) doi:10.1109/CVPR.2001.990960

BibTeX

@inproceedings{srinark2001cvpr-framework,
  title     = {{A Framework for Multiple Snakes}},
  author    = {Srinark, Thitiwan and Kambhamettu, Chandra},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2001},
  pages     = {II:202-209},
  doi       = {10.1109/CVPR.2001.990960},
  url       = {https://mlanthology.org/cvpr/2001/srinark2001cvpr-framework/}
}