Robust Affine Invariant Matching with Application to Line Features

Tsai, Frank C. D.

doi:10.1109/CVPR.1993.341100

Robust Affine Invariant Matching with Application to Line Features

Frank C. D. Tsai

CVPR 1993 pp. 393-399

doi:10.1109/CVPR.1993.341100 /cvpr/1993/tsai1993cvpr-robust/

Abstract

Line features in geometric hashing are discussed. Lines are used as the primitive features to compute the geometric invariants, combining the Hough transform with a variation of geometric hashing as a technique for model-based object recognition in seriously degraded single intensity images. The effect of uncertainty of line features on the computed invariants for the case where images are formed under affine viewing transformations is analytically determined. The system is implemented with experiments on polygonal objects, which are modeled by lines. It is shown that the technique is noise resistant and suitable in an environment containing many occlusions.< <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

Tsai. "Robust Affine Invariant Matching with Application to Line Features." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1993. doi:10.1109/CVPR.1993.341100

Markdown

[Tsai. "Robust Affine Invariant Matching with Application to Line Features." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1993.](https://mlanthology.org/cvpr/1993/tsai1993cvpr-robust/) doi:10.1109/CVPR.1993.341100

BibTeX

@inproceedings{tsai1993cvpr-robust,
  title     = {{Robust Affine Invariant Matching with Application to Line Features}},
  author    = {Tsai, Frank C. D.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1993},
  pages     = {393-399},
  doi       = {10.1109/CVPR.1993.341100},
  url       = {https://mlanthology.org/cvpr/1993/tsai1993cvpr-robust/}
}