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Unsupervised Extraction of Salient Region-Descriptors for Content Based Image Retrieval

A.Dimai
Proceedings of the 10th International Conference on Image Analysis and Processing
September 1999

Abstract

Several content based image retrieval systems use region-based descriptors of salient regions to represent the image content. In this application domain, no perfect pixel wise segmentation is required, but instead, a stable and unsupervised extraction of salient region-descriptors is needed which might be generally applicable. Accordingly, in this paper an algorithm is proposed which combines local and area-based information of multidimensional features, such as luminance, color and texture to extract robustly region-descriptors of salient regions. Furthermore, the selection of the corresponding regions is parameter-free thus ensuring its general applicability. The algorithm is easy to extend to other feature types and has been used to extract salient regions from images of a large database consisting of outdoor scenes.


Download in postscript format
@InProceedings{eth_biwi_00167,
  author = {A.Dimai},
  title = {Unsupervised Extraction of Salient Region-Descriptors for Content Based Image Retrieval},
  booktitle = {Proceedings of the 10th International Conference on Image Analysis and Processing},
  year = {1999},
  month = {September},
  keywords = {segmentation, recognition, image indexing, database, matching, edges}
}