Automatic name extraction from degraded document images

  • Authors:
  • Laurence Likforman-Sulem;Pascal Vaillant;Aliette de Bodard de la Jacopière

  • Affiliations:
  • Ecole Nationale Supérieure des Télécommunications/TSI and CNRS-LTCI, 46 rue Barrault, 75013, Paris, France;Ecole Nationale Supérieure des Télécommunications/TSI and CNRS-LTCI, Paris, France and Université des Antilles-Guyane, Institut d’Enseignement Supérieur d ...;Ecole Nationale Supérieure des Télécommunications/TSI and CNRS-LTCI, 46 rue Barrault, 75013, Paris, France

  • Venue:
  • Pattern Analysis & Applications
  • Year:
  • 2006

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Abstract

The problem addressed in this paper is the automatic extraction of names from a document image. Our approach relies on the combination of two complementary analyses. First, the image-based analysis exploits visual clues to select the regions of interest in the document. Second, the textual-based analysis searches for name patterns and low-level word textual features. Both analyses are then combined at the word level through a neural network fusion scheme. Reported results on degraded documents such as facsimile and photocopied technical journals demonstrate the interest of the combined approach.