Retrieval of Partially Visible Shapes through Structural Feature Indexing

  • Hirobumi Nishida
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1876)


Efficient and robust information retrieval from large image databases is an essential functionality for the reuse, manipulation, and editing of multimedia documents. Structural feature indexing is a potential approach to efficient shape retrieval from large image databases, but the indexing is sensitive to noise, scales of observation, and local shape deformations. It has now been confirmed that efficiency of classification and robustness against noise and local shape transformations can be improved through the feature indexing approach incorporating shape feature generation techniques. Based on this approach, an efficient, robust method is presented for retrieval of model shapes that have parts similar to the query shape presented to the image database. Effectiveness is confirmed through experimental trials with a large database of boundary contours, and is validated by systematically designed experiments with a large number of synthetic data.


Structural Indexing Image Database Model Shape Characteristic Number Shape Signature 
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 2000

Authors and Affiliations

  • Hirobumi Nishida
    • 1
  1. 1.Ricoh Software Research CenterTokyoJapan

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