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International Conference on Image Analysis and Processing

ICIAP 2022: Image Analysis and Processing – ICIAP 2022 pp 211–224Cite as

Digital Line Segment Detection for Table Reconstruction in Document Images

Part of the Lecture Notes in Computer Science book series (LNCS,volume 13232)

Abstract

Table detection is often involved in many applications of document analysis as tables are frequently used to present structured information. In this context, we are interested in extracting table regions in document images. More precisely, we propose a method for table detection based on a recent edge line detector which is developed in the context of digital geometry and it allows to handle noisy document images. The extracted lines are then used to reconstruct the tables contained in the image. The method has been evaluated and compared to other state-of-the-art methods and shown a very competitive result.

Keywords

  • Line detector
  • Blurred segment
  • Adaptive directional scan
  • Materialized table extraction
  • Digital geometry

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Notes

  1. 1.

    A similar line model has been used in [14] for line verification and table extraction. Their model consists in separating the 1D intensity profile, from left to right, into 3 zones: the intensity should begin to increase then (potentially) stabilize and decrease.

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Author information

Authors and Affiliations

  1. Université de Lorraine, CNRS, LORIA, 54000, Nancy, France

    Phuc Ngo

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  1. Phuc Ngo
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Correspondence to Phuc Ngo .

Editor information

Editors and Affiliations

  1. Boston University, Boston, MA, USA

    Prof. Stan Sclaroff

  2. National Research Council, Lecce, Italy

    Cosimo Distante

  3. National Research Council, Lecce, Italy

    Marco Leo

  4. University of Catania, Catania, Italy

    Dr. Giovanni M. Farinella

  5. Technische Universität München, Garching, Germany

    Prof. Dr. Federico Tombari

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Ngo, P. (2022). Digital Line Segment Detection for Table Reconstruction in Document Images. In: Sclaroff, S., Distante, C., Leo, M., Farinella, G.M., Tombari, F. (eds) Image Analysis and Processing – ICIAP 2022. ICIAP 2022. Lecture Notes in Computer Science, vol 13232. Springer, Cham. https://doi.org/10.1007/978-3-031-06430-2_18

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  • DOI: https://doi.org/10.1007/978-3-031-06430-2_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-06429-6

  • Online ISBN: 978-3-031-06430-2

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