Daniel P. Lopresti
“Style-Based Ballot Mark Recognition,” P. Xiu, D.
Lopresti, H. Baird, G. Nagy, and E. Barney Smith, to be presented at
the Tenth International Conference
on Document Analysis and
Recognition, July 2009, Barcelona, Spain.
Abstract
The push toward voting via hand-marked paper ballots has focused
attention on the limitations of current optical scan systems.
Discrepancies between human and machine interpretations of ballot
markings can lead to a loss of trust in the election process. In this
paper, a style-based approach to ballot recognition is proposed in
which marks are recognized collectively rather than in isolation. The
consistency of a voter’s style is leveraged to improve the overall
accuracy of the system. We compare style-based recognition to various
kinds of singlet classifiers and show that it outperforms them by a
substantial margin.
Paper ( PDF 81 kbytes)
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