DocumentCode
1994188
Title
Using character recognition and segmentation to tell computer from humans
Author
Simard, Patrice Y. ; Szeliski, Richard ; Benaloh, Josh ; Couvreur, Julien ; Calinov, Iulian
Author_Institution
One Microsoft Way, Redmond, WA, USA
fYear
2003
fDate
3-6 Aug. 2003
Firstpage
418
Abstract
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.
Keywords
Internet; biometrics (access control); character recognition; character sets; electronic mail; electronic messaging; human computer interaction; image segmentation; interactive systems; optical character recognition; ASCII string; Hotmail registration system; Human Interactive Proof systems; Internet; MSN; OCR algorithms; OCR research; character segmentation; human character recognition; human faculty; online polls; random distorted characters; Character recognition; Costs; Detectors; Hip; Humans; Image segmentation; Internet; Optical character recognition software; Pattern recognition; Text recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Document Analysis and Recognition, 2003. Proceedings. Seventh International Conference on
Print_ISBN
0-7695-1960-1
Type
conf
DOI
10.1109/ICDAR.2003.1227701
Filename
1227701
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