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Permanent link (DOI): https://doi.org/10.7939/R3028PD1Q

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On random field CAPTCHA generation Open Access

Descriptions

Author or creator
Kouritzin, Michael
Newton, F.
Wu, B.
Additional contributors
Subject/Keyword
statistical information compression
simulation
security
Markov random field
image processing
Type of item
Journal Article (Published)
Language
English
Place
Time
Description
Herein, we propose generating CAPTCHAs through random field simulation and give a novel, effective and efficient algorithm to do so. Indeed, we demonstrate that sufficient information about word tests for easy human recognition is contained in the site marginal probabilities and the site-to-nearby-site covariances and these quantities can be embedded into KNW conditional proba- bilities, designed for effective simulation. The CAPTCHAs are then partial random realizations of the random CAPTCHA word: we start with an initial random field (e.g., randomly scattered letter pieces) and use Gibbs resampling to re-simulate portions of the field repeatedly using the KNW conditional probabilities until the word becomes human-readable. The residual randomness from the initial random field together with the random implementation of the CAPTCHA word provide significant resistance to attack. This results in a CAPTCHA which is unrecognizable to modern OCR but is recognized about 95% of the time in a human readability study.
Date created
2013
DOI
doi:10.7939/R3028PD1Q
License information
Rights
© 2013 IEEE Transactions on Image Processing. This version of this article is open access and can be downloaded and shared. The original author(s) and source must be cited.
Citation for previous publication
M. A. Kouritzin, F. Newton and B. Wu. (2013). " On random field CAPTCHA generation '', IEEE Transactions on Image Processing 22(4), pp. 1656-1666.
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