A k-max geodesic distance and its application in image segmentation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86095834" target="_blank" >RIV/61989100:27240/15:86095834 - isvavai.cz</a>

Výsledek na webu

<a href="http://link.springer.com/chapter/10.1007%2F978-3-319-23192-1_52" target="_blank" >http://link.springer.com/chapter/10.1007%2F978-3-319-23192-1_52</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-23192-1_52" target="_blank" >10.1007/978-3-319-23192-1_52</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A k-max geodesic distance and its application in image segmentation

Popis výsledku v původním jazyce

The geodesic distance is commonly used when solving image processing problems. In noisy images, unfortunately, it often gives unsatisfactory results. In this paper, we propose a new k-max geodesic distance. The length of path is defined as the sum of thek maximum edge weights along the path. The distance is defined as the length of the path that is the shortest one in this sense. With an appropriate choice of the value of k, the influence of noise can be reduced substantially. The positive properties are demonstrated on the problem of seeded image segmentation. The results are compared with the results of geodesic distance and with the results of the random walker segmentation algorithm. The influence of k value is also discussed.

Název v anglickém jazyce

A k-max geodesic distance and its application in image segmentation

Popis výsledku anglicky

The geodesic distance is commonly used when solving image processing problems. In noisy images, unfortunately, it often gives unsatisfactory results. In this paper, we propose a new k-max geodesic distance. The length of path is defined as the sum of thek maximum edge weights along the path. The distance is defined as the length of the path that is the shortest one in this sense. With an appropriate choice of the value of k, the influence of noise can be reduced substantially. The positive properties are demonstrated on the problem of seeded image segmentation. The results are compared with the results of geodesic distance and with the results of the random walker segmentation algorithm. The influence of k value is also discussed.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

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 9256

ISBN

978-3-319-23191-4

ISSN

0302-9743

e-ISSN

—

Počet stran výsledku

12

Strana od-do

618-629

Název nakladatele

Springer Verlag

Místo vydání

London

Místo konání akce

Valletta

Datum konání akce

2. 9. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000364705500052