Detail publikace

Texture Image Description for Content Based Image Retrieval

HECKEL, M.

Originální název

Texture Image Description for Content Based Image Retrieval

Anglický název

Texture Image Description for Content Based Image Retrieval

Jazyk

en

Originální abstrakt

Content based image retrieval systems use for description of image queries and images in a database their own color, texture and shape properties. This paper focuses on the description of texture properties of images. A technique for texture image description is proposed, which consists of two steps: an analysis of particular texture samples obtained by an image uniform sampling followed by the k-means algorithm, which is applied for partitioning feature vectors from this analysis into image regions. The use of this approach is also presented, mainly in respect of natural textures with a size gradient. This technique was used in an experimental texture retrieval system too. An example of a query and a retrieval result are included as well.

Anglický abstrakt

Content based image retrieval systems use for description of image queries and images in a database their own color, texture and shape properties. This paper focuses on the description of texture properties of images. A technique for texture image description is proposed, which consists of two steps: an analysis of particular texture samples obtained by an image uniform sampling followed by the k-means algorithm, which is applied for partitioning feature vectors from this analysis into image regions. The use of this approach is also presented, mainly in respect of natural textures with a size gradient. This technique was used in an experimental texture retrieval system too. An example of a query and a retrieval result are included as well.

Dokumenty

BibTex 


@inproceedings{BUT10022,
  author="Martin {Heckel}",
  title="Texture Image Description for Content Based Image Retrieval",
  annote="Content based image retrieval systems use for description of image queries and images in a database their own color, texture and shape properties. This paper focuses on the description of texture properties of images. A technique for texture image description is proposed, which consists of two steps: an analysis of particular texture samples obtained by an image uniform sampling followed by the k-means algorithm, which is applied for partitioning feature vectors from this analysis into image regions. The use of this approach is also presented, mainly in respect of natural textures with a size gradient. This technique was used in an experimental texture retrieval system too. An example of a query and a retrieval result are included as well.",
  address="Faculty of Electrical Engineering and Communication BUT",
  booktitle="Proceedings of 8th Conference Student EEICT 2002",
  chapter="10022",
  edition="3",
  institution="Faculty of Electrical Engineering and Communication BUT",
  year="2002",
  month="may",
  pages="450--454",
  publisher="Faculty of Electrical Engineering and Communication BUT",
  type="conference paper"
}