Distortion estimation techniques in solving visual CAPTCHAs

  • Authors:
  • Gabriel Moy;Nathan Jones;Curt Harkless;Randall Potter

  • Affiliations:
  • Areté Associates, Sherman Oaks, CA;Areté Associates, Sherman Oaks, CA;Areté Associates, Sherman Oaks, CA;Areté Associates, Sherman Oaks, CA

  • Venue:
  • CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
  • Year:
  • 2004

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Abstract

This paper describes two distortion estimation techniques for object recognition that solve EZ-Gimpy and Gimpy-r, two of the visual CAPTCHAs ("Completely Automated Public Turing test to tell Computers and Humans Apart") with high degrees of success. A CAPTCHA is a program that generates and grades tests that most humans can pass but current computer programs cannot pass. We have developed a correlation algorithm that correctly identifies the word in an EZ-Gimpy challenge image 99% of the time and a direct distortion estimation algorithm that correctly identifies the four letters in a Gimpy-r challenge image 78% of the time.