An introduction to splines for use in computer graphics & geometric modeling
An introduction to splines for use in computer graphics & geometric modeling
Fast Algorithms for Low-Level Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
LeRec: a NN/HMM hybrid for on-line handwriting recognition
Neural Computation
Digital Image Warping
Human Interactive Proofs and Document Image Analysis
DAS '02 Proceedings of the 5th International Workshop on Document Analysis Systems V
Telling humans and computers apart automatically
Communications of the ACM - Information cities
Designing human friendly human interaction proofs (HIPs)
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
ScatterType: A Legible but Hard-to-Segment CAPTCHA
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Embedded noninteractive continuous bot detection
Computers in Entertainment (CIE) - Theoretical and Practical Computer Applications in Entertainment
A mailbox ownership based mechanism for curbing spam
Computer Communications
Email Spam Filtering: A Systematic Review
Foundations and Trends in Information Retrieval
A low-cost attack on a Microsoft captcha
Proceedings of the 15th ACM conference on Computer and communications security
A highly legible CAPTCHA that resists segmentation attacks
HIP'05 Proceedings of the Second international conference on Human Interactive Proofs
Segmentation of Arabic Characters: A Comprehensive Survey
International Journal of Technology Diffusion
FaceDCAPTCHA: Face detection based color image CAPTCHA
Future Generation Computer Systems
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How do you tell a computer from a human? Thesituation arises often on the Internet, when online pollsare conducted, accounts are requested, undesired email isreceived, and chat-rooms are spammed. The approachwe use is to create a visual challenge that is easy forhumans but difficult for a computer. More specifically,our challenge is to recognize a string of randomdistorted characters. To pass the challenge, the subjectmust type in the correct corresponding ASCII string.From an OCR point of view, this problem is interestingbecause our goal is to use the vast amount ofaccumulated knowledge to defeat the state of the art OCRalgorithms. This is a role reversal from traditional OCRresearch.Unlike many other systems, our algorithm is based onthe assumption that segmentation is much more difficultthan recognition. Our image challenges present hardsegmentation problems that humans are particularly aptat solving. The technology is currently being used inMSN's Hotmail registration system, where it hassignificantly reduced daily registration rate with minimalConsumer Support impact.