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Using Character Recognition and Segmentation to Tell Computer from Humans

Patrice Y. Simard, Richard Szeliski, Josh Benaloh, Julien Couvreur, and Iulian Calinov


How do you tell a computer from a human? The situation arises often on the Internet, when online polls are conducted, accounts are requested, undesired email is received, and chat-rooms are spammed. The approach we use is to create a visual challenge that is easy for humans but difficult for a computer. More specifically, our challenge is to recognize a string of random distorted characters. To pass the challenge, the subject must type in the correct corresponding ASCII string. From an OCR point of view, this problem is interesting because our goal is to use the vast amount of accumulated knowledge to defeat the state of the art OCR algorithms. This is a role reversal from traditional OCR research.

Unlike many other systems, our algorithm is based on the assumption that segmentation is much more difficult than recognition. Our image challenges present hard segmentation problems that humans are particularly apt at solving. The technology is currently being used in MSN’s Hotmail registration system, where it has significantly reduced daily registration rate with minimal Consumer Support impact.


Publication typeInproceedings
Published in7th International Conference on Document Analysis and Recognition
AddressEdinburgh, Scotland
PublisherIEEE Computer Society Press
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