<div class="csl-bib-body">
<div class="csl-entry">Banaeyan, M., Carratù, C., Kropatsch, W., & Hladůvka, J. (2022). Fast Distance Transforms in Graphs and in Gmaps. In <i>Structural, Syntactic, and Statistical Pattern Recognition</i> (pp. 193–202). https://doi.org/10.1007/978-3-031-23028-8_20</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/142191
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dc.description.abstract
Distance Transform (DT) as a fundamental operation in pattern recognition computes how far inside a shape a point is located. In this paper, at first, a novel method is proposed to compute the DT in a graph. By using the edge classification and a total order, the spanning forest of the foreground is created where distances are propagated through it. Second, in contrast to common linear DT methods, by exploiting the hierarchical structure of the irregular pyramid, the geodesic DT (GDT) is calculated with parallel logarithmic complexity. Third, we introduce the DT in the nD generalized map (n-Gmap) leading to a more precise and smoother DT. Forth, in the n-Gmap we define n different distances and the relation between these distances. Finally, we sketch how the newly introduced concepts can be used to simulate gas propagation in 2D sections of plant leaves.
en
dc.language.iso
en
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dc.relation.ispartofseries
Lecture Notes in Computer Science
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dc.subject
nD distance transform
en
dc.subject
Generalized maps
en
dc.subject
Irregular pyramids
en
dc.subject
Parallel processing
en
dc.subject
Logarithmic complexity
en
dc.subject
Geodesic distance transform (GDT)
en
dc.title
Fast Distance Transforms in Graphs and in Gmaps
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.contributor.affiliation
TU Wien
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dc.relation.isbn
978-3-031-23028-8
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dc.description.startpage
193
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dc.description.endpage
202
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dc.type.category
Full-Paper Contribution
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tuw.booktitle
Structural, Syntactic, and Statistical Pattern Recognition
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tuw.container.volume
13813
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tuw.peerreviewed
true
-
tuw.researchinfrastructure
Vienna Scientific Cluster
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tuw.researchTopic.id
C4
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tuw.researchTopic.name
Mathematical and Algorithmic Foundations
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tuw.researchTopic.value
100
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tuw.publication.orgunit
E193-03 - Forschungsbereich Virtual and Augmented Reality
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tuw.publisher.doi
10.1007/978-3-031-23028-8_20
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dc.description.numberOfPages
10
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tuw.author.orcid
0000-0001-8621-6424
-
tuw.author.orcid
0000-0001-6942-7625
-
tuw.author.orcid
0000-0003-4915-4118
-
tuw.author.orcid
0000-0002-5947-8813
-
tuw.event.name
Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition (SPR) and Struct 2022
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tuw.event.startdate
26-08-2022
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tuw.event.enddate
27-08-2022
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tuw.event.online
On Site
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tuw.event.type
Event for scientific audience
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tuw.event.place
Montreal
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tuw.event.country
CA
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tuw.event.presenter
Banaeyan, Majid
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wb.sciencebranch
Informatik
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wb.sciencebranch
Mathematik
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wb.sciencebranch.oefos
1020
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wb.sciencebranch.oefos
1010
-
wb.sciencebranch.value
70
-
wb.sciencebranch.value
30
-
item.openairecristype
http://purl.org/coar/resource_type/c_5794
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item.grantfulltext
none
-
item.languageiso639-1
en
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item.cerifentitytype
Publications
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item.fulltext
no Fulltext
-
item.openairetype
conference paper
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crisitem.author.dept
E193-03 - Forschungsbereich Virtual and Augmented Reality
-
crisitem.author.dept
E193-03 - Forschungsbereich Virtual and Augmented Reality
-
crisitem.author.dept
E193-03 - Forschungsbereich Virtual and Augmented Reality
-
crisitem.author.orcid
0000-0001-8621-6424
-
crisitem.author.orcid
0000-0001-6942-7625
-
crisitem.author.parentorg
E193 - Institut für Visual Computing and Human-Centered Technology
-
crisitem.author.parentorg
E193 - Institut für Visual Computing and Human-Centered Technology
-
crisitem.author.parentorg
E193 - Institut für Visual Computing and Human-Centered Technology