Detail publikace

Data Mining and Its Use in Texture Analysis

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 texture primitive level. Within this method, a technique for feature vector construction without a priori knowledge of textures different from the analyzed one is presented. This 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 texture primitive level. Within this method, a technique for feature vector construction without a priori knowledge of textures different from the analyzed one is presented. This contribution also contains some results of texture image segmentation experiments.

BibTex


@inproceedings{BUT10889,
  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 texture primitive level. Within this method, a
technique for feature vector construction without a priori knowledge of
textures different from the analyzed one is presented. This
contribution also contains some results of texture image segmentation
experiments.",
  address="Warsaw University",
  booktitle="Proceedings of the CS&P'2003 Workshop",
  chapter="10889",
  institution="Warsaw University",
  year="2003",
  month="september",
  pages="225--234",
  publisher="Warsaw University",
  type="conference paper"
}