Document analysis support for the manual auditing of elections

Daniel Lopresti, Xiang Zhou, Xiaolei Huang, Gang Tan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recent developments have resulted in dramatic changes in the way elections are conducted, both in the United States and around the world. Well-publicized flaws in the security of electronic voting systems have led to a push for the use of verifiable paper records in the election process. In this paper, we describe the application of document analysis techniques to facilitate the manual auditing of elections, both to assure the reliability of the final outcome as well as to help reconcile the differences that may arise between repeated scans of the same ballot. We show how techniques developed for document duplicate detection can be applied to this problem, and present experimental results that demonstrate the efficacy of our approach. Related issues concerning machine support for the auditing of elections are also discussed.

Original languageEnglish (US)
Title of host publicationICDAR2009 - 10th International Conference on Document Analysis and Recognition
Pages733-737
Number of pages5
DOIs
StatePublished - 2009
EventICDAR2009 - 10th International Conference on Document Analysis and Recognition - Barcelona, Spain
Duration: Jul 26 2009Jul 29 2009

Publication series

NameProceedings of the International Conference on Document Analysis and Recognition, ICDAR
ISSN (Print)1520-5363

Other

OtherICDAR2009 - 10th International Conference on Document Analysis and Recognition
Country/TerritorySpain
CityBarcelona
Period7/26/097/29/09

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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