Detail publikace

IMMI: Interactive Segmentation Toolkit

MAŠEK, J. BURGET, R. UHER, V.

Originální název

IMMI: Interactive Segmentation Toolkit

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

General image segmentation is a non–trivial task, which requires significant computational power and huge amount of knowledge incorporated. Fortunately, it is not necessary in all the cases. In some specific cases, simpler non–supervised or supervised segmentation methods can be used giving even better results. In this paper, a novel trainable segmentation method based on RapidMiner data–mining platform is introduced, and its functionality is described. The method implementation was released under open–source license as a part of IMMI (IMage MIning) extension of the RapidMiner platform. When compared to other trainable segmentation algorithms, the platform provides flexibility connected with all the features of one of the most widely used data–mining platform today. The functionality has been verified on the satellite image use–case, accuracy achieving 78.3% pixel error.

Klíčová slova

Classification, image segmentation, interactive tool, IMMI, RapidMiner

Autoři

MAŠEK, J.; BURGET, R.; UHER, V.

Rok RIV

2013

Vydáno

15. 9. 2013

Nakladatel

Springer Berlin Heidelberg

Místo

Heidelberg

ISBN

978-3-642-41012-3

Kniha

Engineering Applications of Neural Networks

ISSN

1865-0929

Periodikum

Communications in Computer and Information Science

Ročník

383

Číslo

24

Stát

Spolková republika Německo

Strany od

380

Strany do

387

Strany počet

510

BibTex

@inproceedings{BUT101149,
  author="Jan {Mašek} and Radim {Burget} and Václav {Uher}",
  title="IMMI: Interactive Segmentation Toolkit",
  booktitle="Engineering Applications of Neural Networks",
  year="2013",
  journal="Communications in Computer and Information Science",
  volume="383",
  number="24",
  pages="380--387",
  publisher="Springer Berlin Heidelberg",
  address="Heidelberg",
  doi="10.1007/978-3-642-41013-0\{_}39",
  isbn="978-3-642-41012-3",
  issn="1865-0929"
}