Ballot Mark Detection

Elisa H. Barney Smith, Boise State University
Daniel Lopresti, Lehigh University
George Nagy, Rensselaer Polytechnic Institute

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This document was originally published by IEEE in International Conference on Pattern Recognition. Copyright restrictions may apply.
doi: 10.1109/ICPR.2008.4761549

Abstract

Optical mark sensing, i.e., detecting whether a “bubble” has been filled in, may seem straightforward. However, on US election ballots the shape, intensity, size and position of the marks, while specified, are highly variable due to a diverse electorate. The ballots may be produced and scanned by poorly maintained equipment. Yet near-perfect results are required. To improve the current technology, which has been subject to criticism, components of a process for identifying marks on an optical sense ballot are evaluated. When marked synthetic ballots are compared to an unmarked ballot, the absolute difference of adaptive thresholded images gives best detection rates for all darknesses of marks, but at a false alarm rate increase. Simple absolute differencing can give good detection results with lower false alarm rates.