Towards Improved Paper-Based Election Technology

Elisa H. Barney Smith; Daniel Lopresti; George Nagy; Ziyan Wu

doi:10.1109/ICDAR.2011.253

Towards Improved Paper-Based Election Technology

Elisa H. Barney Smith, Daniel Lopresti, George Nagy, Ziyan Wu

Electrical Engineering Department

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

Resources are presented for fostering paper-based election technology. They comprise a diverse collection of real and simulated ballot and survey images, and software tools for ballot synthesis, registration, segmentation, and ground-truthing. The grids underlying the designated location of voter marks are extracted from 13,315 degraded ballot images. The actual skew angles of sample ballots, recorded as part of complete ballot descriptions compiled with the interactive ground-truthing tool, are compared with their automatically extracted parameters. The average error is 0.1 degrees. These results provide a baseline for the application of digital image analysis to the scrutiny of electoral ballots.

Original language	American English
Journal	2011 International Conference on Document Analysis and Recognition (ICDAR)
DOIs	https://doi.org/10.1109/ICDAR.2011.253
State	Published - 18 Sep 2011

Keywords

ballot data
ballot readers
challenged Minnesota ballots
document segmentation
elections
mark recognition

EGS Disciplines

Electrical and Computer Engineering

Access to Document

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http://dx.doi.org/10.1109/ICDAR.2011.253

Cite this

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title = "Towards Improved Paper-Based Election Technology",

abstract = " Resources are presented for fostering paper-based election technology. They comprise a diverse collection of real and simulated ballot and survey images, and software tools for ballot synthesis, registration, segmentation, and ground-truthing. The grids underlying the designated location of voter marks are extracted from 13,315 degraded ballot images. The actual skew angles of sample ballots, recorded as part of complete ballot descriptions compiled with the interactive ground-truthing tool, are compared with their automatically extracted parameters. The average error is 0.1 degrees. These results provide a baseline for the application of digital image analysis to the scrutiny of electoral ballots.",

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author = "{Barney Smith}, {Elisa H.} and Daniel Lopresti and George Nagy and Ziyan Wu",

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AU - Barney Smith, Elisa H.

AU - Lopresti, Daniel

AU - Nagy, George

AU - Wu, Ziyan

PY - 2011/9/18

Y1 - 2011/9/18

N2 - Resources are presented for fostering paper-based election technology. They comprise a diverse collection of real and simulated ballot and survey images, and software tools for ballot synthesis, registration, segmentation, and ground-truthing. The grids underlying the designated location of voter marks are extracted from 13,315 degraded ballot images. The actual skew angles of sample ballots, recorded as part of complete ballot descriptions compiled with the interactive ground-truthing tool, are compared with their automatically extracted parameters. The average error is 0.1 degrees. These results provide a baseline for the application of digital image analysis to the scrutiny of electoral ballots.

AB - Resources are presented for fostering paper-based election technology. They comprise a diverse collection of real and simulated ballot and survey images, and software tools for ballot synthesis, registration, segmentation, and ground-truthing. The grids underlying the designated location of voter marks are extracted from 13,315 degraded ballot images. The actual skew angles of sample ballots, recorded as part of complete ballot descriptions compiled with the interactive ground-truthing tool, are compared with their automatically extracted parameters. The average error is 0.1 degrees. These results provide a baseline for the application of digital image analysis to the scrutiny of electoral ballots.

KW - ballot data

KW - ballot readers

KW - challenged Minnesota ballots

KW - document segmentation

KW - elections

KW - mark recognition

UR - https://scholarworks.boisestate.edu/electrical_facpubs/180

U2 - 10.1109/ICDAR.2011.253

DO - 10.1109/ICDAR.2011.253

M3 - Article

JO - 2011 International Conference on Document Analysis and Recognition (ICDAR)

JF - 2011 International Conference on Document Analysis and Recognition (ICDAR)

ER -

Towards Improved Paper-Based Election Technology

Abstract

Keywords

EGS Disciplines

Access to Document

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