Document Analysis Techniques for Automatic Electoral Document Processing: A Survey

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9269)


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.


Document image analysis Computer vision Paper ballots Paper based elections Optical scan Tally 



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.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Scytl Secure Electronic VotingBarcelonaSpain
  2. 2.Computer Vision CenterUniversitat Autònoma de BarcelonaBarcelonaSpain

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