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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.

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)

© 2004 P.C. Rossin College of Engineering & Applied Science
Computer Science & Engineering, Packard Laboratory, Lehigh University, Bethlehem PA 18015