ML Anthology

On the Congruence of Noisy Images to Line Segment Models

Ingemar J. Cox, Joseph B. Kruskal
ICCV 1988 pp. 252-258
doi:10.1109/CCV.1988.589996 /iccv/1988/cox1988iccv-congruence/

Abstract

An algorithm is described for matching two-dimensional images that does not depend on the extraction of features, a step which is often difficult or impractical. It combines computational efficiency with robustness against noisy data. It has been tested with two kinds of data. The algorithm matches a two-dimensional image, in the form of a set of points, to a line segment model. It estimates a positive congruence (i.e., a translation plus a rotation) that moves the image onto the model. The algorithm is most appropriate for matching when the required congruence is small, and it seems very well suited to motion-tracking. Experimental results have been obtained for two kinds of images: (1) points obtained from an optical range finder, and (2) edge points extracted from an intensity image. Only the former results are presented.

ICCV Semantic Scholar

Cite

Text

Cox and Kruskal. "On the Congruence of Noisy Images to Line Segment Models." IEEE/CVF International Conference on Computer Vision, 1988. doi:10.1109/CCV.1988.589996

Markdown

[Cox and Kruskal. "On the Congruence of Noisy Images to Line Segment Models." IEEE/CVF International Conference on Computer Vision, 1988.](https://mlanthology.org/iccv/1988/cox1988iccv-congruence/) doi:10.1109/CCV.1988.589996

BibTeX

@inproceedings{cox1988iccv-congruence,
  title     = {{On the Congruence of Noisy Images to Line Segment Models}},
  author    = {Cox, Ingemar J. and Kruskal, Joseph B.},
  booktitle = {IEEE/CVF International Conference on Computer Vision},
  year      = {1988},
  pages     = {252-258},
  doi       = {10.1109/CCV.1988.589996},
  url       = {https://mlanthology.org/iccv/1988/cox1988iccv-congruence/}
}