2D Captchas from 3D Models

Existing image-based Captchas (completely automated public tests to tell computers and humans apart) utilize huge, public image databases to limit access to Websites via image matching attacks. In this paper, a different image based Captcha was developed and prototyped to address the mislabeling and other shortcomings of traditional schemes, which utilize huge public image databases. A database was populated with n 3D models. Then, random rotations, distortions, translations, lighting effects and warping were applied resulting in 2D images. Those 2D images were presented to users for identification to gain access to a Website. Users are prompted to identify the object with the label provided through a menu bar. This approach creates an infinite number of 2D images from a 3D model. Therefore, it appears to be impractical for an intruder to algorithmic ally identify the resulting 2D image without resorting to random guesses

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