Fuzzy Convergence
Abstract
This work considers the problem of discovering areas of convergence of line-like shapes in an image. The motivating application is to use the convergence of the blood vessel network to automatically locate the optic nerve in an ocular fundus image. A fuzzy segment model is proposed, based on a conjecture that line-like shapes only contribute to a perception of convergence in their near neighborhood. Using this model, a voting-type method is described to compute a convergence image, which can be searched for one absolute, or one or more relative, strongest points of convergence. Results are presented for twenty ocular fundus images, with a 65% success rate for finding the optic nerve.
Cite
Text
Hoover and Goldbaum. "Fuzzy Convergence." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1998. doi:10.1109/CVPR.1998.698682Markdown
[Hoover and Goldbaum. "Fuzzy Convergence." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1998.](https://mlanthology.org/cvpr/1998/hoover1998cvpr-fuzzy/) doi:10.1109/CVPR.1998.698682BibTeX
@inproceedings{hoover1998cvpr-fuzzy,
title = {{Fuzzy Convergence}},
author = {Hoover, Adam W. and Goldbaum, Michael H.},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {1998},
pages = {716-721},
doi = {10.1109/CVPR.1998.698682},
url = {https://mlanthology.org/cvpr/1998/hoover1998cvpr-fuzzy/}
}