Meaningful Scales Detection: an Unsupervised Noise Detection Algorithm for Digital Contours
Bertrand Kerautret, Jacques-Olivier Lachaud
→ BibTeX
@article{ipol.2014.75,
    title   = {{Meaningful Scales Detection: an Unsupervised Noise Detection Algorithm for Digital Contours}},
    author  = {Kerautret, Bertrand and Lachaud, Jacques-Olivier},
    journal = {{Image Processing On Line}},
    volume  = {4},
    pages   = {98--115},
    year    = {2014},
    doi     = {10.5201/ipol.2014.75},
}
% if your bibliography style doesn't support doi fields:
    note    = {\url{https://doi.org/10.5201/ipol.2014.75}}
published
2014-05-07
reference
Bertrand Kerautret, and Jacques-Olivier Lachaud, Meaningful Scales Detection: an Unsupervised Noise Detection Algorithm for Digital Contours, Image Processing On Line, 4 (2014), pp. 98–115. https://doi.org/10.5201/ipol.2014.75

Communicated by Bertrand Kerautret
Demo edited by Bertrand Kerautret

Abstract

This work presents an algorithm which permits to detect locally on digital contour what is the amount of noise estimated from a given maximal scale. The method is based on the asymptotic properties of the length of the maximal segment primitive.

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