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Differences of Global Features for Region Indexing

177, 1997
ETH Zurich


There is an immense number of possible queries, if an image should be retrieved by its subregions from a large image database. Therefore an index which encodes the spatial information of an image, should make only a few assumption about possible queries. In addition, the index has to consider the different scales of objects in an image. The proposed index, which encodes images regions, is an hierarchical index, gained by a fixed partition. The information of each region is represented by global features. But in the index only the distances of these features to the global features of the whole image are stored. The suggested index uses color features and is easy to implement. The index is tested on a database with more than 12'000 images.

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  author = {A.~Dimai},
  title = {Differences of Global Features for Region Indexing},
  year = {1997},
  month = {February},
  number = {177},
  institution = {ETH Zurich},
  keywords = {image indexing, matching, recognition, database}