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Asian Conference on Computer Vision

ACCV 1998: Computer Vision — ACCV'98 pp 105–112Cite as

Document categorization for document image understanding

  • Poster Session II
  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1352))

Abstract

In the knowledge-based document image understanding, it is important to distinguish the layout structures of individual documents exactly with a view to making use of adaptable document model. At least, the document models which are characterized heuristically by the application-specific layout structures are not always applicable to every document. In this paper, we propose a categorization method of various kinds of documents. Our categorization method on the basis of the classification and verification paradigm divides various kinds of documents into appropriate document types stepwisely. First, the classification procedure divides the given documents using rough features about documents, and then the verification procedure is applied to the globally categorized document sets, using the detail features.

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References

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Author information

Author notes

  1. Hiroyuki Masai

    Present address: R & D Group, Media Lab., OKI Electronic Industry Co.,Ltd., Higashiasakawa-cho, 550-5, Hachioji, Tokyo, Japan

Authors and Affiliations

  1. Department of Information Engineering, Graduate School of Engineering, Nagoya University, Furo-cho, 464-01, Chikusa-ku, Nagoya, Japan

    Hiroyuki Masai & Toyohide Watanabe

Authors
  1. Hiroyuki Masai
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  2. Toyohide Watanabe
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Editor information

Roland Chin Ting-Chuen Pong

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© 1997 Springer-Verlag Berlin Heidelberg

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Masai, H., Watanabe, T. (1997). Document categorization for document image understanding. In: Chin, R., Pong, TC. (eds) Computer Vision — ACCV'98. ACCV 1998. Lecture Notes in Computer Science, vol 1352. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63931-4_204

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  • DOI: https://doi.org/10.1007/3-540-63931-4_204

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63931-2

  • Online ISBN: 978-3-540-69670-4

  • eBook Packages: Springer Book Archive

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