Detail publikace
Data Mining and Its Use in Texture Analysis
HECKEL, M., ZENDULKA, J.
Originální název
Data Mining and Its Use in Texture Analysis
Anglický název
Data Mining and Its Use in Texture Analysis
Jazyk
en
Originální abstrakt
This paper deals with an idea of the use of data mining approach in texture analysis. A new method based on association rules is proposed. This method utilizes the multiresolution analysis of an analyzed image texture and works at the texture primitive level. Within this method, a technique for feature vector construction without any a priori knowledge of textures different from the analyzed one is presented. The contribution also contains some results of texture image segmentation experiments.
Anglický abstrakt
This paper deals with an idea of the use of data mining approach in texture analysis. A new method based on association rules is proposed. This method utilizes the multiresolution analysis of an analyzed image texture and works at the texture primitive level. Within this method, a technique for feature vector construction without any a priori knowledge of textures different from the analyzed one is presented. The contribution also contains some results of texture image segmentation experiments.
Dokumenty
BibTex
@article{BUT45715,
author="Martin {Heckel} and Jaroslav {Zendulka}",
title="Data Mining and Its Use in Texture Analysis",
annote="This paper deals with an idea of the use of data mining approach in
texture analysis. A new method based on association rules is proposed.
This method utilizes the multiresolution analysis of an analyzed image
texture and works at the texture primitive level. Within this method, a
technique for feature vector construction without any a priori
knowledge of textures different from the analyzed one is presented. The
contribution also contains some results of texture image segmentation
experiments.",
address="IOS Press",
booktitle="Fundamenta Informaticae",
chapter="45715",
institution="IOS Press",
journal="Fundamenta Informaticae",
number="60",
volume="2004",
year="2004",
month="april",
pages="173--186",
publisher="IOS Press",
type="journal article - other"
}