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Leveraging the mixed-text segmentation problem to design secure handwritten CAPTCHAs

  • SUNY Buffalo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

In this paper we present a novel CAPTCHA that is based on the current hard AI problem of mixed-text (handwriting and printed-text) segmentation. The proposed CAPTCHA overlays generated handwritten word images on a generated printed-text background. We first propose a modification that allows for character level perturbations on an existing synthetic handwriting generation technique. These perturbations are parameterized allowing for varying levels of handwritten word complexity. We then use the output from the modified synthetic handwriting generator as the foreground for the mixed-text CAPTCHA. Experiments show that the proposed approach is effective at successfully distinguishing between humans and machines. Human recognition accuracy averages at 0.77 while machine accuracy is below 0.0001.

Original languageEnglish
Title of host publicationProceedings - 12th International Conference on Frontiers in Handwriting Recognition, ICFHR 2010
Pages13-18
Number of pages6
DOIs
StatePublished - 2010
Event12th International Conference on Frontiers in Handwriting Recognition, ICFHR 2010 - Kolkata, India
Duration: Nov 16 2010Nov 18 2010

Publication series

NameProceedings - 12th International Conference on Frontiers in Handwriting Recognition, ICFHR 2010

Conference

Conference12th International Conference on Frontiers in Handwriting Recognition, ICFHR 2010
Country/TerritoryIndia
CityKolkata
Period11/16/1011/18/10

Keywords

  • Human interactive proofs
  • Mixed-text segmentation
  • Text-based CAPTCHAs

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