Texture Based Segmentation Using Graph Cut and Gabor Filters

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F11%3A43898223" target="_blank" >RIV/49777513:23520/11:43898223 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1134/S105466181102043X" target="_blank" >http://dx.doi.org/10.1134/S105466181102043X</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1134/S105466181102043X" target="_blank" >10.1134/S105466181102043X</a>

Result language

angličtina

Original language name

Texture Based Segmentation Using Graph Cut and Gabor Filters

Original language description

This paper describes a method for texture based segmentation. Texture features are extracted by applying a bank of Gabor filters using two-sided convolution strategy. Probability texture model is represented by Gaussian mixture that is trained with the Expectation-maximization algorithm. Texture similarity, obtained this way, is used like the input of a Graph cut method. We show that the combination of texture analysis and the Graph cut method produce good results.

Czech name

—

Czech description

—

Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

JD - Use of computers, robotics and its application

OECD FORD branch

—

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2011

Confidentiality

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

Name of the periodical

Pattern Recognition and Image Analysis

ISSN

1054-6618

e-ISSN

—

Volume of the periodical

21

Issue of the periodical within the volume

2

Country of publishing house

DE - GERMANY

Number of pages

4

Pages from-to

258-261

UT code for WoS article

—

EID of the result in the Scopus database

—