Optimal keys for image database indexing

  • Michael S. Lew
  • D. P. (Nies) Huijsmans
  • Dee Denteneer
Poster Session C: Compression, Hardware & Software, Databases, Neural Networks, Object Recognition & Reconstruction
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1311)

Abstract

This paper examines the problem of efficient indexing of large image databases using the theory of optimal keys. The methods based on optimal keys are compared empirically with a texture classification method and template matching for benchmarking purposes in the Leiden WWW color image database and the 19th century portrait database. The different indexing methods are compared and evaluated in the problem space of finding copies of corrupted images. Real world noise is present in the form of print-scanner noise and general image degradation.

Keywords

Local Binary Pattern Image Database Template Match Corrupted Image Ranking Error 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Michael S. Lew
    • 1
  • D. P. (Nies) Huijsmans
    • 1
  • Dee Denteneer
    • 2
  1. 1.Department of Computer ScienceLeiden UniversityRA LeidenNetherlands
  2. 2.Philips Research LaboratoryAA Eindhoven

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