Paper
17 January 2005 ScatterType: a reading CAPTCHA resistant to segmentation attack
Henry S. Baird, Terry P. Riopka
Author Affiliations +
Proceedings Volume 5676, Document Recognition and Retrieval XII; (2005) https://doi.org/10.1117/12.587811
Event: Electronic Imaging 2005, 2005, San Jose, California, United States
Abstract
A reading-based CAPTCHA designed to resist character-segmentation attacks, called 'ScatterType,' is described. Its challenges are pseudorandomly synthesized images of text strings rendered in machine-print typefaces: within each image, characters are fragmented using horizontal and vertical cuts, and the fragments are scattered by vertical and horizontal displacements. This scattering is designed to defeat all methods known to us for automatic segmentation into characters. As in the BaffleText CAPTCHA, English-like but unspellable text-strings are used to defend against known-dictionary attacks. In contrast to the PessimalPrint and BaffleText CAPTCHAs (and others), no physics-based image degradations, occlusions, or extraneous patterns are employed. We report preliminary results from a human legibility trial with 57 volunteers that yielded 4275 CAPTCHA challenges and responses. ScatterType human legibility remains remarkably high even on extremely degraded cases. We speculate that this is due to Gestalt perception abilities assisted by style-specific (here, typeface-specific) consistency among primitive shape features of character fragments. Although recent efforts to automate style-consistent perceptual skills have reported progress, the best known methods do not yet pose a threat to ScatterType. The experimental data also show that subjective rating of difficulty is strongly (and usefully) correlated with illegibility. In addition, we present early insights emerging from these data as we explore the ScatterType design space -- choice of typefaces, 'words', cut positioning, and displacements -- with the goal of locating regimes in which ScatterType challenges remain comfortably legible to almost all people but strongly resist mahine-vision methods for automatic segmentation into characters.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Henry S. Baird and Terry P. Riopka "ScatterType: a reading CAPTCHA resistant to segmentation attack", Proc. SPIE 5676, Document Recognition and Retrieval XII, (17 January 2005); https://doi.org/10.1117/12.587811
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Cited by 63 scholarly publications.
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KEYWORDS
Image segmentation

Scattering

Optical character recognition

Machine vision

Computer engineering

Computer science

Defense and security

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