An automatic initialization of interactive segmentation methods using shortest path basins

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F16%3A43929877" target="_blank" >RIV/49777513:23520/16:43929877 - isvavai.cz</a>

Výsledek na webu

<a href="http://link.springer.com/article/10.1134/S1054661816020188" target="_blank" >http://link.springer.com/article/10.1134/S1054661816020188</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1134/S1054661816020188" target="_blank" >10.1134/S1054661816020188</a>

Jazyk výsledku

angličtina

Název v původním jazyce

An automatic initialization of interactive segmentation methods using shortest path basins

Popis výsledku v původním jazyce

Image segmentation is one of many fundamental problems in computer vision. The need to divide an image to a number of classes is often a part of a system that uses image processing methods. Therefore, lots of methods were developed that are based on different approaches. The image segmentation could be classified with respect to many criteria. One such a criterion is based on the degree of allowed interactivity. The interactivity could be of several types-interactive initialization, interaction while the computation is running or manual refinement of achieved results, for example. Especially the precise initialization plays an important role in many methods. Therefore the possibility to initialize the method manually is often invaluable advantage and information obtained this way could be the difference between good and poor results. Unfortunately, in many cases it is not possible to initialize a method manually and the process needs to be automated. In this paper, an approach for such an automation is presented. It is based on shortest paths in a graph and deriving an area of influence for each obtained seed point. This method is called shortest path basins.

Název v anglickém jazyce

An automatic initialization of interactive segmentation methods using shortest path basins

Popis výsledku anglicky

Image segmentation is one of many fundamental problems in computer vision. The need to divide an image to a number of classes is often a part of a system that uses image processing methods. Therefore, lots of methods were developed that are based on different approaches. The image segmentation could be classified with respect to many criteria. One such a criterion is based on the degree of allowed interactivity. The interactivity could be of several types-interactive initialization, interaction while the computation is running or manual refinement of achieved results, for example. Especially the precise initialization plays an important role in many methods. Therefore the possibility to initialize the method manually is often invaluable advantage and information obtained this way could be the difference between good and poor results. Unfortunately, in many cases it is not possible to initialize a method manually and the process needs to be automated. In this paper, an approach for such an automation is presented. It is based on shortest paths in a graph and deriving an area of influence for each obtained seed point. This method is called shortest path basins.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

—

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název periodika

Pattern Recognition and Image Analysis

ISSN

1054-6618

e-ISSN

—

Svazek periodika

26

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

RU - Ruská federace

Počet stran výsledku

7

Strana od-do

336-342

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-84975833222