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Automatic name extraction from degraded document images

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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.

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Acknowledgements

We thank the French Ministry of the Economy, Finance and Industry (MINEFI) which has been supported this work under Grant no : 01.2.93.0268. This work could not have been possible without the competent help of François Yvon of the ENST Computer Science Department, who devoted much of his time during the first stage of this project to provide us with advice, guidance, and scientific experience. The authors also wish to thank Noura Azzabou for her assistance in the experiments.

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  1. Pascal Vaillant

    Present address: Université des Antilles-Guyane, Institut d’Enseignement Supérieur de Guyane, Campus de Saint-Denis, Avenue d’Estrées, B.P. 792, 97337, Cayenne cedex, Guyane française

Authors and Affiliations

  1. Ecole Nationale Supérieure des Télécommunications/TSI and CNRS-LTCI, 46 rue Barrault, 75013, Paris, France

    Laurence Likforman-Sulem, Pascal Vaillant & Aliette de Bodard de la Jacopière

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  1. Laurence Likforman-Sulem
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  2. Pascal Vaillant
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  3. Aliette de Bodard de la Jacopière
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Correspondence to Laurence Likforman-Sulem.

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Likforman-Sulem, L., Vaillant, P. & de Bodard de la Jacopière, A. Automatic name extraction from degraded document images. Pattern Anal Applic 9, 211–227 (2006). https://doi.org/10.1007/s10044-006-0038-6

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