Efficient User-Guided Ballot Image Verification

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.