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A Local Structure Matching Approach for Large Image Database Retrieval

  • Yanling Chi
  • Maylor K. H. Leung
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3211)

Abstract

The combination of a local structure based shape representation and a histogram based indexing structure is proposed to fast localize objects from large database. Four novel geometric attributes are extracted from each local structure. They are invariant to translation, scaling, rotation and robust to adverse distortions and noise. The search space is pruned by means of histogram intersection and the computation cost of the query is linear to the number of input features. The matching is performed by a non-metric similarity measure with regard to significance in reconstruction of query image and discrimination of different models. The concepts proposed were tested on thousands of images. The result manifests its efficiency and effectiveness.

Keywords

Local Structure Indexing Structure Query Image Zernike Moment Shape Match 
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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Yanling Chi
    • 1
  • Maylor K. H. Leung
    • 1
  1. 1.School of Computer EngineeringNanyang Technological UniversitySingapore

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