Content based Image Retrieval using Interest Points and Texture Features (bibtex)
by Christian Wolf
Abstract:
Content based image retrieval is the task of searching images from a database, which are visually similar to a given example image. Since there is no general definition for visual similarity, there are different possible ways to query for visual content. In this work we present methods for content based image retrieval based on texture similarity using interest points and Gabor features. Interest point detectors are used in computer vision to detect image points with special properties, which can be geometric (corners) or non-geometric (contrast etc.). Gabor functions and Gabor filters are regarded as excellent tools for texture feature extraction and texture segmentation. We present methods how to combine these methods for content based image retrieval and to generate a texture description of images. Special emphasis is devoted to distance measures for the texture descriptions. Experimental results of the query system on different test image databases are given.
Reference:
Content based Image Retrieval using Interest Points and Texture Features (Christian Wolf), Technical report, PRIP, TU Wien, 2000.
Bibtex Entry:
@TechReport{PTR-Wolf00a,
  author =	 "Christian Wolf",
  institution =	 "PRIP, TU Wien",
  number =	 "PRIP-TR-061",
  title =	 "Content based {I}mage {R}etrieval using {I}nterest
                  {P}oints and {T}exture {F}eatures",
  year =	 "2000",
  url =		 "ftp://ftp.prip.tuwien.ac.at/pub/publications/trs/tr61.ps.gz",
  abstract =	 "Content based image retrieval is the task of
                  searching images from a database, which are visually
                  similar to a given example image. Since there is no
                  general definition for visual similarity, there are
                  different possible ways to query for visual
                  content. In this work we present methods for content
                  based image retrieval based on texture similarity
                  using interest points and Gabor features. Interest
                  point detectors are used in computer vision to
                  detect image points with special properties, which
                  can be geometric (corners) or non-geometric
                  (contrast etc.). Gabor functions and Gabor filters
                  are regarded as excellent tools for texture feature
                  extraction and texture segmentation. We present
                  methods how to combine these methods for content
                  based image retrieval and to generate a texture
                  description of images. Special emphasis is devoted
                  to distance measures for the texture
                  descriptions. Experimental results of the query
                  system on different test image databases are given.",
}
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