Talks and Poster Presentations (with Proceedings-Entry):

I. Janusch, N. Artner, W. Kropatsch:
"Euclidean and Geodesic Distance Profiles";
Talk: DGCI 20th International Conference on Discrete Geometry for Computer Imagery 2017, Wien; 2017-09-19 - 2017-09-21; in: "International Conference on Discrete Geometry for Computer Imagery DGCI 2017: Discrete Geometry for Computer Imagery", Springer International Publishing, 10502, Vienna, Austria (2017), ISBN: 978-3-319-66271-8; 307 - 318.

English abstract:
This paper presents a boundary-based, topological shape de-
scriptor: the distance profile. It is inspired by the LBP (= local binary
pattern) scale space - a topological shape descriptor computed by a fil-
tration with concentric circles around a reference point. For rigid objects,
the distance profile is computed by the Euclidean distance of each bound-
ary pixel to a reference point. A geodesic distance profile is proposed for
articulated or deformable shapes: the distance is measured by a combina-
tion of the Euclidean distance of each boundary pixel to the nearest pixel
of the shape´s medial axis and the geodesic distance along the shape´s
medial axis to the reference point. In contrast to the LBP scale space, it
is invariant to deformations and articulations and the persistence of the
extrema in the profiles allows pruning of spurious branches (i.e. robust-
ness against noise on the boundary). The distance profiles are applicable
to any shape, but the geodesic distance profile is especially well-suited
for articulated or deformable objects (e.g.applications in biology).

Electronic version of the publication:

Created from the Publication Database of the Vienna University of Technology.