A Novel Form Structure Extraction Method Using Strip Projection
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
ACM SIGGRAPH 2004 Papers
ACM SIGGRAPH 2004 Papers
Document analysis issues in reading optical scan ballots
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
Understanding the security properties of ballot-based verification techniques
EVT/WOTE'09 Proceedings of the 2009 conference on Electronic voting technology/workshop on trustworthy elections
Implementing risk-limiting post-election audits in California
EVT/WOTE'09 Proceedings of the 2009 conference on Electronic voting technology/workshop on trustworthy elections
On optical mark-sense scanning
Towards Trustworthy Elections
An analysis of write-in marks on optical scan ballots
EVT/WOTE'11 Proceedings of the 2011 conference on Electronic voting technology/workshop on trustworthy elections
Operator-assisted tabulation of optical scan ballots
EVT/WOTE'12 Proceedings of the 2012 international conference on Electronic Voting Technology/Workshop on Trustworthy Elections
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Optical scan voting systems are ubiquitous. Unfortunately, optical scan technology is vulnerable to failures that can result in miscounted votes and lost confidence. While manual counts may be able to detect these failures, counting all the ballots by hand is in many situations impractical and prohibitively expensive. In this paper, we present a novel approach for examining a large set of ballot images to verify that they were properly interpreted by the opscan system. Our system allows the user to simultaneously inspect and verify many ballot images at once. In this way, our scheme is significantly more efficient than manually recounting or inspecting ballots one at a time, providing the accuracy associated with human inspection at reduced cost. We evaluate our approach on approximately 30,000 ballots cast in the June 2008 Humboldt County Primary Election and demonstrate that our approach improves the efficiency of human verification of ballot images by an order of magnitude.