2D Filtering of Curvilinear Structures by Ranking the Orientation Responses of Path Operators (RORPO)
Odyssee Merveille, Benoît Naegel, Hugues Talbot, Laurent Najman, Nicolas Passat
→ BibTeX
@article{ipol.2017.207,
    title   = {{2D Filtering of Curvilinear Structures by Ranking the Orientation Responses of Path Operators (RORPO)}},
    author  = {Merveille, Odyssee and Naegel, Benoît and Talbot, Hugues and Najman, Laurent and Passat, Nicolas},
    journal = {{Image Processing On Line}},
    volume  = {7},
    pages   = {246--261},
    year    = {2017},
    doi     = {10.5201/ipol.2017.207},
}
% if your bibliography style doesn't support doi fields:
    note    = {\url{https://doi.org/10.5201/ipol.2017.207}}
published
2017-10-01
reference
Odyssee Merveille, Benoît Naegel, Hugues Talbot, Laurent Najman, and Nicolas Passat, 2D Filtering of Curvilinear Structures by Ranking the Orientation Responses of Path Operators (RORPO), Image Processing On Line, 7 (2017), pp. 246–261. https://doi.org/10.5201/ipol.2017.207

Communicated by Rafael Grompone von Gioi
Demo edited by Thibaud Ehret

Abstract

We present a filtering method for 2D curvilinear structures, called RORPO (Ranking the Orientation Responses of Path Operators). RORPO is based on path operators, a recently developed family of mathematical morphology filters. Compared with state of the art methods, RORPO is non-local and well adapted to the intrinsic anisotropy of curvilinear structures. Since RORPO does not depend on a linear scale-space framework, it tends to preserve object contours without a blurring effect. Due to these properties, RORPO is a useful low-level filter and can also serve as a curvilinear prior in segmentation frameworks. In this article, after introducing RORPO, we develop the 2D version of the algorithm and present a few applications.

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