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Operator-Assisted Tabulation of Optical Scan Ballots

Authors: 

Kai Wang, University of California, San Diego; Nicholas Carlini, Eric Kim, Ivan Motyashov, Daniel Nguyen, and David Wagner, University of California, Berkeley

Abstract: 

We present OpenCount: a system that tabulates scanned ballots from an election by combining computer vision algorithms with focused operator assistance. OpenCount is designed to support risk-limiting audits and to be scalable to large elections, robust to conditions encountered using typical scanner hardware, and general to a wide class of ballot types—all without the need for integration with any vendor systems. To achieve these goals, we introduce a novel operator-in-the-loop computer vision pipeline for automatically processing scanned ballots while allowing the operator to intervene in a simple, intuitive manner. We evaluate our system on data collected from five risk-limiting audit pilots conducted in California in 2011.

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