Image segmentation based on solving the flow in the mesh with the connections of limited capacities

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F17%3A10238517" target="_blank" >RIV/61989100:27240/17:10238517 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007/978-3-319-59876-5_19" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-319-59876-5_19</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-59876-5_19" target="_blank" >10.1007/978-3-319-59876-5_19</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Image segmentation based on solving the flow in the mesh with the connections of limited capacities

Popis výsledku v původním jazyce

This paper presents a novel seeded segmentation technique inspired by the flowing of a liquid in a mesh of pipes. The method can be likened to the anisotropic diffusion algorithm. On the other hand, some substantial changes in the relation of how the diffusion works are included. The method is based on the spreading of liquid from the foreground seeds to the neighboring image points that represent basins with an initial amount of liquid. The background seeds drain the liquid from the neighboring basins. If a basin is full or empty, the corresponding pixel becomes a new source or sink. The algorithm runs until all pixels become either sources or sinks. The properties of the method are illustrated on the image segmentation of synthetic images. The comparison with other segmentation techniques is presented on real-life images. The experiments show promising results of the new method. © Springer International Publishing AG 2017.

Název v anglickém jazyce

Image segmentation based on solving the flow in the mesh with the connections of limited capacities

Popis výsledku anglicky

This paper presents a novel seeded segmentation technique inspired by the flowing of a liquid in a mesh of pipes. The method can be likened to the anisotropic diffusion algorithm. On the other hand, some substantial changes in the relation of how the diffusion works are included. The method is based on the spreading of liquid from the foreground seeds to the neighboring image points that represent basins with an initial amount of liquid. The background seeds drain the liquid from the neighboring basins. If a basin is full or empty, the corresponding pixel becomes a new source or sink. The algorithm runs until all pixels become either sources or sinks. The properties of the method are illustrated on the image segmentation of synthetic images. The comparison with other segmentation techniques is presented on real-life images. The experiments show promising results of the new method. © Springer International Publishing AG 2017.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Lecture Notes in Computer Science. Volume 10317

ISBN

978-3-319-59875-8

ISSN

0302-9743

e-ISSN

neuvedeno

Počet stran výsledku

8

Strana od-do

163-170

Název nakladatele

Springer

Místo vydání

Cham

Místo konání akce

Montréal

Datum konání akce

5. 7. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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