Looking Behind the Captcha-Cracking Scenes

So how does digit fortuity a Captcha? Plain older OCR software, same what comes with your scanner, doesn’t do the job.

I couldn’t intend whatever answers from the Slavonic subsurface accord that’s doing a aggregation of the cracking, but there are whatever albescent hats who expose aspects of their methods.

PWNtcha is a Captcha-cracking send that reports superior success against whatever of the field ones. Its methods are incommunicative lest they artefact discover into the wild, but it seems to refer manually analyzing a Captcha’s style, its type choice, case position, impairment pattern, rotation, background, etc., and then using image-correction tools to alter the ikon into normal-looking text, which crapper be successfully machine-read.

Jeff Yan and Ahmad Salah El Ahmad hit published a PDF describing a segmentation-then-recognition approach. In some cases, evidently, a plain element calculate suffices to surmisal what a letter’s questionable to be: I has more pixels than M.

aiCaptcha dates from 2005.

Here is a communicating of the Shape Contexts move to noise EZ-Gimpy, finished by Mori and Malik backwards in 2002.

I’d be rattling peculiar to see info of the techniques utilised against the such harder Google and Microsoft tests.

See Also:

• Is Captcha’s Moment Passing?
• For Certain Tasks, the Cortex Still Beats the CPU
• ReCaptcha: Fight Spam And Digitize Books

Tags: ahmad, character position, cortex, deformation pattern, font choice, gimpy, google, image correction, job, microsoft, microsoft tests, ocr software, pixel, salah, scanner, segmentation, shape contexts, underground community, white hats, yan

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