Configuration REcognition Model for Complex Reverse Engineering Methods: 2(CREM)

  • Karim Hadjar
  • Oliver Hitz
  • Lyse Robadey
  • Rolf Ingold
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2423)

Abstract

This paper describes 2(CREM), a recognition method to be applied on documents with complex structures allowing incremental learning in an interactive environment. The classification is driven by a model, which contains a static as well as a dynamic part and evolves by use. The first prototype of 2(CREM) has been tested on four different phases of newspaper image analysis: line segment recognition, frame recognition, line merging into blocks, and logical labeling. Some promising experimental results are reported.

References

  1. [1]
    Robert M. Haralick. Document Image Understanding: Geometric and Logical Layout. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pages 385–390, 1994.Google Scholar
  2. [2]
    A. Antonacopoulos B. Gatos, S.L. Mantzaris. First International Newspaper Segmentation Contest. In ICDAR’2001: Sixth International Conference on Document Analysis and Recognition, pages 1190–1194, Seattle, USA, September 2001.Google Scholar
  3. [3]
    B. Gatos, S. L. Mantzaris, K. V. Chandrios, A. Tsigris, and S. J. Perantonis. Integrated Algorithms for Newspaper Page Decomposition and Article Tracking. In ICDAR’99: Fifth International Conference on Document Analysis and Recognition, pages 559–562, Bangalore, India, September 1999.Google Scholar
  4. [4]
    Karim Hadjar, Oliver Hitz, and Rolf Ingold. Newspaper Page Decomposition Using a Split and Merge Approach. In ICDAR’2001: Sixth International Conference on Document Analysis and Recognition, pages 1186–1189, Seattle, USA, September 2001.Google Scholar
  5. [5]
    Pierre Heroux, Eric Trupin, and Yves Lecourtier. Modélisation et classification pour la rétroconversion des documents. In CIFED’2000: Colloque International Francophone sur l’Ecrit et le Document, pages 413–421, Lyon, France, jul 2000.Google Scholar
  6. [6]
    J. Hu, R. Kashi, D. Lopresti, G. Nagy, and G. Wilfong. Why Table Ground Truthing is Hard. In ICDAR’2001: Sixth International Conference on Document Analysis and Recognition, pages 129–133, Seattle, USA, September 2001.Google Scholar
  7. [7]
    Frédéric Bapst. Reconnaissance de documents assisté: architecture logicielle et intégration de savoir-faire. PhD thesis, University of Fribourg, 1998.Google Scholar
  8. [8]
    Oliver Hitz, Lyse Robadey, and Rolf Ingold. An Architecture for Editing Document Recognition Results Using XML. In DAS’2000: 4th International Workshop on Document Analysis Systems, pages 385–396, Rio de Janeiro, Brazil, December 2000.Google Scholar
  9. [9]
    Rolf Brugger, Abdelwahab Zramdini, and Rolf Ingold. Modeling Documents for Structure Recognition Using Generalized N-Grams. In ICDAR’97: Fourth International Conference on Document Analysis and Recognition, pages 56–61, Ulm, Germany, August 1997.Google Scholar
  10. [10]
    Abdelwahab Zramdini. Study of Optical Font Recognition Based on Global Typographical Features. PhD thesis, University of Fribourg, 1995.Google Scholar
  11. [11]
    Lyse Robadey. Une méthode de reconnaissance structurelle de documents complexes basée sur des patterns bidimensionnels. PhD thesis, University of Fribourg, 2001.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Karim Hadjar
    • 1
  • Oliver Hitz
    • 1
  • Lyse Robadey
    • 1
  • Rolf Ingold
    • 1
  1. 1.DIUFUniversity of FribourgFribourgSwitzerland

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