Efficient Retrieval for Browsing Large Image Databases.

Daniel Wu, Divyakant Agrawal, Amr El Abbadi, Ambuj K. Singh, Terence R. Smith: Efficient Retrieval for Browsing Large Image Databases. CIKM 1996: 11-18

@inproceedings{DBLP:conf/cikm/WuAASS96,
  author    = {Daniel Wu and
               Divyakant Agrawal and
               Amr El Abbadi and
               Ambuj K. Singh and
               Terence R. Smith},
  title     = {Efficient Retrieval for Browsing Large Image Databases},
  booktitle = {CIKM '96, Proceedings of the Fifth International Conference on
               Information and Knowledge Management, November 12 - 16, 1996,
               Rockville, Maryland, USA},
  publisher = {ACM},
  year      = {1996},
  pages     = {11-18},
  ee        = {db/conf/cikm/WuAASS96.html, http://doi.acm.org/10.1145/238355.238365},
  crossref  = {DBLP:conf/cikm/96},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Abstract

The Alexandria project has been initiated to build a digital library for map and satellite images. Designed for content-based retrieval, the relevant information in each image is encoded in the form of a multi-dimensional feature vector. Though representing images by feature vectors greatly facilitates user queries, indexing these vectors degrades performance when the number of dimensions is large. We consider 2 popular techniques (DFT and SVD) to reduce the dimension of feature vectors, and study their retrieval performance with respect to recall and precision. We find that though SVD generally out-performs DFT, DFT compares favorably in a limited range suitable for browsing large image databases.

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CIKM '96, Proceedings of the Fifth International Conference on Information and Knowledge Management, November 12 - 16, 1996, Rockville, Maryland, USA. ACM 1996
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