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International Workshop on Graph-Based Representations in Pattern Recognition

GbRPR 2005: Graph-Based Representations in Pattern Recognition pp 23–34Cite as

Graph Transformation in Document Image Analysis: Approaches and Challenges

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3434))

Abstract

Graphs and graph transformation are versatile tools for representing and interpreting the contents of document images. Three main components are involved: a graph representing the contents of a document image at some level of interpretation, a set of graph transformation rules (graph productions), and a mechanism for controlling the application of the graph productions. We review existing document analysis systems that use graph transformation, and discuss challenges and research opportunities in this area.

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Author information

Authors and Affiliations

  1. School of Computing, Queen’s University, Kingston, Ontario, K7L 3N6, Canada

    Dorothea Blostein

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  1. Dorothea Blostein
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Editors and Affiliations

  1. GREYC CNRS UMR 6072, Image Team, Université de Caen Basse-Normandie, 6, Boulevard Maréchal Juin, 14050, Caen Cedex, France

    Luc Brun

  2. Dipartimento di Ingegneria dell’Informazione ed Ingegneria Elettrica, Università di Salerno, via P.te Don Melillo, I-84084, Fisciano, SA), Italy

    Mario Vento

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Blostein, D. (2005). Graph Transformation in Document Image Analysis: Approaches and Challenges. In: Brun, L., Vento, M. (eds) Graph-Based Representations in Pattern Recognition. GbRPR 2005. Lecture Notes in Computer Science, vol 3434. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31988-7_3

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  • DOI: https://doi.org/10.1007/978-3-540-31988-7_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25270-2

  • Online ISBN: 978-3-540-31988-7

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