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Theses and Dissertations

On Random Field CAPTCHA Generation Open Access


Other title
Optical character recognition
Random field
Human readability
Attack resistance
Type of item
Degree grantor
University of Alberta
Author or creator
Newton, Fraser
Supervisor and department
Kouritzin, Michael (Mathematical and Statistical Sciences)
Examining committee member and department
Schmuland, Byron (Mathematical and Statistical Sciences)
Chough, Keumhee Carrière (Mathematical and Statistical Sciences)
Hillen, Thomas (Mathematical and Statistical Sciences)
Department of Mathematical and Statistical Sciences
Date accepted
Graduation date
Master of Science
Degree level
In this thesis, we develop a novel method of generating CAPTCHAs, which are used to protect online resources from abuse by computer agents. We view CAPTCHA generation as random field simulation and construct a CAPTCHA by evolving an initial state via resimulating pixels until the image becomes readable. We empirically demonstrate that this CAPTCHA is easy for humans to read but difficult for computer programs to crack. We describe how to develop variants of this CAPTCHA; in particular, we implement and assess the utility of a grey-level variant. We establish a method of maximizing the effectiveness of a CAPTCHA variant, and perform analysis to determine which properties of the CAPTCHA most effectively differentiate humans and computer programs. We extend the random field used in the CAPTCHA application to multiple dimensions in the context of graph theory, and describe the generic method of applying the random field to suitable problems.
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
Citation for previous publication
M. Kouritzin, F. Newton, and B. Wu, “On Random Field CAPTCHA Generation,” Accepted with Mandatory Minor Revisions to IEEE Trans- actions on Image Processing.F. Newton and M. Kouritzin, “On grey levels in random captcha gener- ation,” in Proceedings of SPIE Visual Information Processing XX, vol. 8056, 2011, pp. 80 560U–80 560U–12.

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File title: Introduction
File title: On Random Field CAPTCHA Generation
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