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Document Analysis Techniques for Automatic Electoral Document Processing: A Survey

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Book cover E-Voting and Identity (Vote-ID 2015)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 9269))

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Abstract

In this paper, we will discuss the most common challenges in electoral document processing and study the different solutions from the document analysis community that can be applied in each case. We will cover Optical Mark Recognition techniques to detect voter selections in the Australian Ballot, handwritten number recognition for preferential elections and handwriting recognition for write-in areas. We will also propose some particular adjustments that can be made to those general techniques in the specific context of electoral documents.

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Acknowledgements

We thank the reviewers for their suggestions and comments. This work has been partially supported by the Spanish project TIN2012-37475-C02-02 and the European project ERC-2010-AdG-20100407-269796 and by the Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement de la Generalitat de Catalunya.

Author information

Authors and Affiliations

  1. Scytl Secure Electronic Voting, Barcelona, Spain

    J. Ignacio Toledo, Jordi Cucurull & Jordi Puiggalí

  2. Computer Vision Center, Universitat Autònoma de Barcelona, Barcelona, Spain

    Alicia Fornés & Josep Lladós

Authors
  1. J. Ignacio Toledo
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  2. Jordi Cucurull
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  3. Jordi Puiggalí
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  4. Alicia Fornés
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  5. Josep Lladós
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Corresponding author

Correspondence to J. Ignacio Toledo .

Editor information

Editors and Affiliations

  1. Bern University of Applied Sciences, Biel, Switzerland

    Rolf Haenni

  2. Bern University of Applied Sciences, Biel, Switzerland

    Reto E. Koenig

  3. Royal Institute of Technology, Stockholm, Sweden

    Douglas Wikström

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Toledo, J.I., Cucurull, J., Puiggalí, J., Fornés, A., Lladós, J. (2015). Document Analysis Techniques for Automatic Electoral Document Processing: A Survey. In: Haenni, R., Koenig, R., Wikström, D. (eds) E-Voting and Identity. Vote-ID 2015. Lecture Notes in Computer Science(), vol 9269. Springer, Cham. https://doi.org/10.1007/978-3-319-22270-7_8

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  • DOI: https://doi.org/10.1007/978-3-319-22270-7_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22269-1

  • Online ISBN: 978-3-319-22270-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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