ML Anthology

Singularity Analysis and Derivative Scale-Space

Frédéric Falzon, Gérard Giraudon
CVPR 1994 pp. 245-250
doi:10.1109/CVPR.1994.323836 /cvpr/1994/falzon1994cvpr-singularity/

Abstract

The scale-space representations and wavelet transform theory have provided us with good singularity detection frameworks. Thanks to such methods, image understanding processes have become more and more powerful. Some computer vision tasks also require a knowledge on the nature of detected singularities. We propose, in this paper, to take into account these requirements, and we present a singularity detection method based on fractional calculus arguments.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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Cite

Text

Falzon and Giraudon. "Singularity Analysis and Derivative Scale-Space." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1994. doi:10.1109/CVPR.1994.323836

Markdown

[Falzon and Giraudon. "Singularity Analysis and Derivative Scale-Space." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1994.](https://mlanthology.org/cvpr/1994/falzon1994cvpr-singularity/) doi:10.1109/CVPR.1994.323836

BibTeX

@inproceedings{falzon1994cvpr-singularity,
  title     = {{Singularity Analysis and Derivative Scale-Space}},
  author    = {Falzon, Frédéric and Giraudon, Gérard},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1994},
  pages     = {245-250},
  doi       = {10.1109/CVPR.1994.323836},
  url       = {https://mlanthology.org/cvpr/1994/falzon1994cvpr-singularity/}
}