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Asian Conference on Computer Vision

ACCV 1995: Recent Developments in Computer Vision pp 561–569Cite as

Graph grammar based object recognition for image retrieval

  • Content-Based Retrieval
  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1035))

Abstract

In order to retrieve a set of intended images from an image archive, human beings think of special contents with respect to the searched scene. The necessity of a semantics-based retrieval leads to a content-based analysis and retrieval of images. From this point of view, our project Image Retrieval for Information Systems (IRIS) develops and combines methods and techniques of computer vision and knowledge representation in a new way in order to automatically generate textual content descriptions of images. IRIS retrieves the images using a conventional text retrieval system.

This paper concentrates on the discussion of formalization knowledge for modeling concepts and on object recognition by graph grammars.

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Author information

Author notes

  1. Christoph Klauck

    Present address: , P. O. Box 330 440, D-28334, Bremen

Authors and Affiliations

  1. FB 3 - Computer Science - AG KI, University of Bremen, Bremen

    Christoph Klauck

Authors
  1. Christoph Klauck
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Editor information

Stan Z. Li Dinesh P. Mital Eam Khwang Teoh Han Wang

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© 1996 Springer-Verlag Berlin Heidelberg

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Klauck, C. (1996). Graph grammar based object recognition for image retrieval. In: Li, S.Z., Mital, D.P., Teoh, E.K., Wang, H. (eds) Recent Developments in Computer Vision. ACCV 1995. Lecture Notes in Computer Science, vol 1035. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60793-5_109

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  • DOI: https://doi.org/10.1007/3-540-60793-5_109

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60793-9

  • Online ISBN: 978-3-540-49448-5

  • eBook Packages: Springer Book Archive

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